{ "total": 599, "topics": [ { "id": 163414, "title": "Competition Recap - Congratulations to our Winners!", "comment_count": 10, "views": 0, "votes": 53 }, { "id": 155399, "title": "`sales_train_evaluation.csv` now available", "comment_count": 27, "views": 0, "votes": 47 }, { "id": 133465, "title": "New to Machine Learning or Kaggle?", "comment_count": 51, "views": 0, "votes": 30 }, { "id": 133473, "title": "Welcome to the M5 Competitions!", "comment_count": 40, "views": 0, "votes": 32 }, { "id": 740300, "title": "Walmart Business 360 — post-competition forecasting and decision analytics (original code, MIT)", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 715552, "title": "XGBoost Demand Forecasting with Outlier Treatment — Retail Business Context", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 715380, "title": "Weekly demand forecasting: Should I train on weekly or daily data and then aggregate?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 151058, "title": "State Space Models (and/or LightGBM / LSTM)", "comment_count": 1, "views": 0, "votes": 7 }, { "id": 442060, "title": "PGP Thread", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 438301, "title": "Could you please provide any information about promotion part in the dataset?", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163916, "title": "5th place solution", "comment_count": 8, "views": 0, "votes": 43 }, { "id": 133834, "title": "Evaluation metric", "comment_count": 56, "views": 0, "votes": 249 }, { "id": 163183, "title": "54th place solution [No lottery - just a baseline]", "comment_count": 10, "views": 0, "votes": 24 }, { "id": 146326, "title": "ARIMA model in scikit-learn?", "comment_count": 16, "views": 0, "votes": 9 }, { "id": 150568, "title": "It's all about upvotes and medals", "comment_count": 254, "views": 0, "votes": 259 }, { "id": 141972, "title": "4 Strategies for Multi-Step Time Series Forecasting", "comment_count": 4, "views": 0, "votes": 8 }, { "id": 133463, "title": "Some Past Time Series Competitions", "comment_count": 14, "views": 0, "votes": 105 }, { "id": 164374, "title": "3rd place solution - NN approach", "comment_count": 26, "views": 0, "votes": 87 }, { "id": 163684, "title": "1st place solution", "comment_count": 79, "views": 0, "votes": 265 }, { "id": 153518, "title": "Tweedie Distribution by Department", "comment_count": 1, "views": 0, "votes": 8 }, { "id": 134732, "title": "First Competition? Say Hi!", "comment_count": 227, "views": 0, "votes": 50 }, { "id": 134707, "title": "Hierarchical Time Series Resources", "comment_count": 17, "views": 0, "votes": 62 }, { "id": 163216, "title": "4th place solution", "comment_count": 50, "views": 0, "votes": 154 }, { "id": 164599, "title": "2nd place solution", "comment_count": 18, "views": 0, "votes": 68 }, { "id": 133474, "title": "Related Kaggle time series competitions", "comment_count": 9, "views": 0, "votes": 57 }, { "id": 140564, "title": "Some Objective Function for LightGBM", "comment_count": 24, "views": 0, "votes": 105 }, { "id": 173046, "title": "Did anyone use weather and validated that it actually helped?", "comment_count": 4, "views": 0, "votes": 5 }, { "id": 154117, "title": "M5 – are we forecasting for forecasting sake? ", "comment_count": 7, "views": 0, "votes": 4 }, { "id": 166814, "title": "Competition Summary", "comment_count": 8, "views": 0, "votes": 30 }, { "id": 163145, "title": "Some thoughts about nn! (can get top30)", "comment_count": 6, "views": 0, "votes": 5 }, { "id": 159052, "title": "Entity Embeddings For Categorical Features and Neural Networks Idea.", "comment_count": 3, "views": 0, "votes": 5 }, { "id": 228555, "title": "Looking for teammates", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 163211, "title": "14th place solution", "comment_count": 6, "views": 0, "votes": 41 }, { "id": 196244, "title": "Actual values for the evaluation set? ", "comment_count": 6, "views": 0, "votes": 4 }, { "id": 210829, "title": "An article about my solution for this competition.", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 144067, "title": "Three shades of Dark", "comment_count": 66, "views": 0, "votes": 245 }, { "id": 138881, "title": "Few thoughts about M5 competition", "comment_count": 152, "views": 0, "votes": 300 }, { "id": 133469, "title": "Papers from the M4 Competition", "comment_count": 22, "views": 0, "votes": 122 }, { "id": 200739, "title": "M5 Forecast - actual evaluation/winning submissions labels as a Kaggle Dataset?", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 164685, "title": "21st Place Solution (Nodalpoints)", "comment_count": 3, "views": 0, "votes": 17 }, { "id": 142874, "title": "Trend predicting model supplementing tree-based models?", "comment_count": 2, "views": 0, "votes": 17 }, { "id": 160170, "title": "What is M5 merger deadline?", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 135713, "title": "Time Series Forecasting Kernels", "comment_count": 8, "views": 0, "votes": 44 }, { "id": 165497, "title": "Private labels ?", "comment_count": 2, "views": 0, "votes": null }, { "id": 163621, "title": "Shake Up Explained", "comment_count": 30, "views": 0, "votes": 55 }, { "id": 186968, "title": "Exact Accuracy(MAPE)", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163408, "title": "Can we have evaluation labels disclosing?", "comment_count": 4, "views": 0, "votes": 29 }, { "id": 151869, "title": "Rapids xgboost tips", "comment_count": 13, "views": 0, "votes": 37 }, { "id": 163578, "title": "[68th place] Stable solution", "comment_count": 10, "views": 0, "votes": 30 }, { "id": 173803, "title": "Is there a way to see my Private score after the competition ends?", "comment_count": 1, "views": 0, "votes": null }, { "id": 174371, "title": "Rank 172, sharing code for the first time.", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 169085, "title": "16th Place Solution - Kalman Filters and Boosted Trees", "comment_count": 1, "views": 0, "votes": 19 }, { "id": 156912, "title": "so confused about cross validation in lgbm", "comment_count": 6, "views": 0, "votes": 2 }, { "id": 169776, "title": "Centric disbalancing phenomena", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 141545, "title": "Lag(7) - Overfitting?", "comment_count": 9, "views": 0, "votes": 9 }, { "id": 167431, "title": "H20's Driverless AI placed 189, LBM placed 1st and 14th, what's the explanation?", "comment_count": 4, "views": 0, "votes": null }, { "id": 135449, "title": "Hierarchical time series in Python", "comment_count": 7, "views": 0, "votes": 50 }, { "id": 163206, "title": "Speechless... (219th writeup)", "comment_count": 39, "views": 0, "votes": 120 }, { "id": 166444, "title": "`item_id` can be separable?", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 164315, "title": "111th Place Solution (7th on Public) - Key Ideas", "comment_count": 5, "views": 0, "votes": 11 }, { "id": 166127, "title": "My dumb random forest broke the top 50%", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 166148, "title": "The most curious thing I have had about the data", "comment_count": 1, "views": 0, "votes": 4 }, { "id": 164826, "title": "7th place solution", "comment_count": 3, "views": 0, "votes": 17 }, { "id": 163564, "title": "25th place solution", "comment_count": 2, "views": 0, "votes": 13 }, { "id": 165056, "title": "Negative sales ? ", "comment_count": 7, "views": 0, "votes": 0 }, { "id": 163503, "title": "Some ideas to share", "comment_count": 4, "views": 0, "votes": 17 }, { "id": 163346, "title": "[36th place] New forecasting Package: tsboost", "comment_count": 4, "views": 0, "votes": 25 }, { "id": 165673, "title": "Feels bad man!", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 164187, "title": "103rd place (silver medal) solution", "comment_count": 2, "views": 0, "votes": 11 }, { "id": 163199, "title": "Top 1% solution (28th)", "comment_count": 4, "views": 0, "votes": 25 }, { "id": 163379, "title": "[109th place] No Dark Magic, Just ML", "comment_count": 4, "views": 0, "votes": 19 }, { "id": 163127, "title": "[84th place] No multiplier", "comment_count": 11, "views": 0, "votes": 24 }, { "id": 163756, "title": "It was a trap", "comment_count": 5, "views": 0, "votes": 10 }, { "id": 164693, "title": "Adjusting coefficient seems to be unpredictible due to stochastic cannibalization effect", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 163190, "title": "Not a lottery. What -almost- everyone didn't get about the \"multiplier\".", "comment_count": 22, "views": 0, "votes": 24 }, { "id": 163999, "title": "Not a Shake-up Scatter Plot", "comment_count": 0, "views": 0, "votes": 13 }, { "id": 163154, "title": "Top 3% simple solution", "comment_count": 2, "views": 0, "votes": 41 }, { "id": 163047, "title": "Have no idea what's going on...", "comment_count": 29, "views": 0, "votes": 33 }, { "id": 163410, "title": "Top 15 countries under rank 300", "comment_count": 4, "views": 0, "votes": 35 }, { "id": 163372, "title": "[178th Place] Recursive Model with Regression & Classification", "comment_count": 8, "views": 0, "votes": 19 }, { "id": 163659, "title": "M 5.0 or Earthquake 5.0? Why Magic multiplier was a bad idea?", "comment_count": 6, "views": 0, "votes": 9 }, { "id": 164065, "title": "[64th Place] A simple low computation model", "comment_count": 2, "views": 0, "votes": 8 }, { "id": 163376, "title": "Solutions Collection [To Be Updated...]", "comment_count": 2, "views": 0, "votes": 13 }, { "id": 133551, "title": "Beating M4's Winner Score: N-BEATS ", "comment_count": 14, "views": 0, "votes": 85 }, { "id": 163234, "title": "[34th Place Solution] Silver Lining only ( Not on LB anymore )", "comment_count": 7, "views": 0, "votes": 10 }, { "id": 163460, "title": "59th place solution - there is nothing special", "comment_count": 3, "views": 0, "votes": 18 }, { "id": 161718, "title": "Some tips to get better your RMSSE accuracy", "comment_count": 12, "views": 0, "votes": 30 }, { "id": 163474, "title": "175 position in M5 Forecasting - Accuracy", "comment_count": 2, "views": 0, "votes": 9 }, { "id": 163631, "title": "Post-processing for the win!!!", "comment_count": 6, "views": 0, "votes": 5 }, { "id": 163208, "title": "A few thoughts - 24th Place", "comment_count": 1, "views": 0, "votes": 16 }, { "id": 163030, "title": "The end is near...", "comment_count": 9, "views": 0, "votes": 28 }, { "id": 164124, "title": "# of Entries M5 vs. Rossmann Store Sales: Over fitting or Simple Models", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 163259, "title": "This is the 4th recent competition with medal-zone public notebooks", "comment_count": 13, "views": 0, "votes": 7 }, { "id": 163664, "title": "My M5 conclusion", "comment_count": 5, "views": 0, "votes": 7 }, { "id": 163595, "title": "Success with Hierarchical Models?", "comment_count": 4, "views": 0, "votes": 5 }, { "id": 163203, "title": "From Public LB #3762 --> Private LB #80... How I got there", "comment_count": 4, "views": 0, "votes": 18 }, { "id": 163210, "title": "I don't know that I have to select the submission to the final scoring", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 163057, "title": "Random LB or real Shake Up ?", "comment_count": 8, "views": 0, "votes": 17 }, { "id": 163070, "title": "How those ppl submitted a result 3 month ago and still get a silver metal?", "comment_count": 13, "views": 0, "votes": 9 }, { "id": 163046, "title": "Not shakeup at all! It's a mess. Random LB :( ", "comment_count": 3, "views": 0, "votes": 10 }, { "id": 163221, "title": "123rd place solution", "comment_count": 1, "views": 0, "votes": 12 }, { "id": 163189, "title": "Group k-fold works (102nd solution)", "comment_count": 0, "views": 0, "votes": 10 }, { "id": 163248, "title": "Trust Your CV - The Unborn Child [71st in parallel universe]", "comment_count": 4, "views": 0, "votes": 6 }, { "id": 162850, "title": "Best Score with Day to Day Model", "comment_count": 13, "views": 0, "votes": 6 }, { "id": 163052, "title": "Silver Medal Solution", "comment_count": 6, "views": 0, "votes": 5 }, { "id": 163233, "title": "[Place 99] A few insights (no multiplier)", "comment_count": 4, "views": 0, "votes": 12 }, { "id": 163078, "title": "[181th place] Silver medal at the lottery (no multiplier)", "comment_count": 3, "views": 0, "votes": 15 }, { "id": 163161, "title": "Feels like a lottery", "comment_count": 4, "views": 0, "votes": 5 }, { "id": 163184, "title": "Best Private Score did you select it ?", "comment_count": 4, "views": 0, "votes": 3 }, { "id": 163075, "title": "Classification Boost of 0.02", "comment_count": 11, "views": 0, "votes": 5 }, { "id": 163060, "title": "A baseline model got the bronze!", "comment_count": 3, "views": 0, "votes": 8 }, { "id": 163176, "title": "Should have been a \"roll forward\" kernels competitions?", "comment_count": 3, "views": 0, "votes": 8 }, { "id": 163268, "title": "63rd place solution", "comment_count": 1, "views": 0, "votes": 12 }, { "id": 160190, "title": "Just a suggestion :)", "comment_count": 19, "views": 0, "votes": 36 }, { "id": 163186, "title": "What I learned from this competition", "comment_count": 3, "views": 0, "votes": 6 }, { "id": 163092, "title": "Top 4% Solution (221st) - Four Insights", "comment_count": 2, "views": 0, "votes": 10 }, { "id": 163491, "title": "I am missing in the leaderboard", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 163636, "title": "Which cv strategy do you think is better?", "comment_count": 1, "views": 0, "votes": null }, { "id": 163490, "title": "My takes from this competiotn ", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 163085, "title": "Where is my submission?", "comment_count": 13, "views": 0, "votes": 3 }, { "id": 163094, "title": "Overnight Expert", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 163370, "title": "All the things tried", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 163150, "title": "Bias vs Variance", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 163532, "title": "Awesome, congrats", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 162312, "title": "forcasting and reality", "comment_count": 1, "views": 0, "votes": 7 }, { "id": 163386, "title": "Early Stopping/Number of iteration Confusion", "comment_count": 2, "views": 0, "votes": null }, { "id": 163064, "title": " Uncertainty better forcasting metric than accuracy? ", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 163045, "title": "Is this real shakeup?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 163333, "title": "[112th Place] How I missed Rank 2 of M5-Accuracy by a factor!!!", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 162875, "title": "M5 Competition Questionnaire", "comment_count": 1, "views": 0, "votes": 6 }, { "id": 163116, "title": "CA_3 Magic", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 163228, "title": "lost output files of my notebook after the end of M5", "comment_count": 6, "views": 0, "votes": null }, { "id": 163401, "title": "The reason for huge shake-up (My thought)", "comment_count": 5, "views": 0, "votes": null }, { "id": 163063, "title": "The biggest lotto draw competition", "comment_count": 4, "views": 0, "votes": 3 }, { "id": 162854, "title": "Public LB vs Private LB ?", "comment_count": 3, "views": 0, "votes": 2 }, { "id": 162556, "title": "Will this competition have the biggest leaderboard shake ?", "comment_count": 8, "views": 0, "votes": 2 }, { "id": 162463, "title": "Basic question on tuning hyperparameters in M5", "comment_count": 10, "views": 0, "votes": 1 }, { "id": 141469, "title": "Dynamic plotting of time-series with matplotlib", "comment_count": 15, "views": 0, "votes": 58 }, { "id": 163053, "title": "My third medal :)", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 163359, "title": "Walmart m5 Data Normalization from scratch in Kotlin", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163098, "title": "Data preprocessing", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 163279, "title": "My solution, and yet another magic multiplier story..", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 163250, "title": "Missing in the LB", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 162134, "title": "How to play the lottery at Uncertainty", "comment_count": 2, "views": 0, "votes": 19 }, { "id": 163202, "title": "Late Submissions", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 163200, "title": "Congrats to Winner and all folks for efforts !", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163134, "title": "What is the value?", "comment_count": 1, "views": 0, "votes": null }, { "id": 163132, "title": "AutoML Comparisons: Did anyone use any of the AutoML Models for M5 Forecasting Challenge. What is the Score that you got? ", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163096, "title": "Prediction multiplier", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 163043, "title": "Zesus, is `_validation`(d1914~d1941) part counted in Private board?", "comment_count": 3, "views": 0, "votes": null }, { "id": 162094, "title": "Score after submission for evaluation", "comment_count": 7, "views": 0, "votes": 3 }, { "id": 163013, "title": "last question about file", "comment_count": 3, "views": 0, "votes": null }, { "id": 162726, "title": "How to get Feature Correlation Coefficients?", "comment_count": 2, "views": 0, "votes": null }, { "id": 150614, "title": "Why tweedie works?", "comment_count": 14, "views": 0, "votes": 107 }, { "id": 151927, "title": "Recursive, direct, and hybrid modeling", "comment_count": 5, "views": 0, "votes": 51 }, { "id": 162221, "title": "Till when will the notebooks for the competition be available?", "comment_count": 1, "views": 0, "votes": null }, { "id": 162431, "title": "Evaluation Exception: Submission does not contain correct Ids. See sample_submission for correct values.", "comment_count": 6, "views": 0, "votes": 1 }, { "id": 160414, "title": "Melting the Dataset and Time lagged Features", "comment_count": 6, "views": 0, "votes": 1 }, { "id": 162267, "title": "External weather data", "comment_count": 5, "views": 0, "votes": null }, { "id": 161519, "title": "yet another basic question: behavior of negative binomial loss?", "comment_count": 5, "views": 0, "votes": 7 }, { "id": 161845, "title": "Leaderboard", "comment_count": 2, "views": 0, "votes": null }, { "id": 160613, "title": "Why Normalization is not required for tree based models", "comment_count": 9, "views": 0, "votes": 6 }, { "id": 160366, "title": "a basic question on training for time series forecast problem", "comment_count": 5, "views": 0, "votes": 10 }, { "id": 159659, "title": "Dose google colab stop sharing 25 Gig RAM for free?", "comment_count": 4, "views": 0, "votes": 5 }, { "id": 161161, "title": "Submission Format", "comment_count": 7, "views": 0, "votes": null }, { "id": 161584, "title": "How to calculate Weighted RMSSE (WRMSSE) ?", "comment_count": 3, "views": 0, "votes": 2 }, { "id": 161107, "title": "M4 competition result and findings", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 161167, "title": "Custom Pytorch Dataset for Sliding Window batches of train and test data", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 159881, "title": "Code for making the 12 aggregations levels", "comment_count": 4, "views": 0, "votes": 6 }, { "id": 161108, "title": "Residual LSTM", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 161022, "title": "Understanding about Prediction intervals: Quantiles/Quartiles", "comment_count": 1, "views": 0, "votes": -2 }, { "id": 161021, "title": "Understanding aggregation/hierarchical levels", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 160914, "title": "ERROR: Could not parse '' into expected type of Double (Line 57737, Column 461)", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 160680, "title": "Different types of modelling for time series forecasting.", "comment_count": 2, "views": 0, "votes": null }, { "id": 155950, "title": "Tree based models and non starionary time-series", "comment_count": 22, "views": 0, "votes": 12 }, { "id": 160475, "title": "Can we use tensorflow Bidirectional LSTM model for the forecasting?", "comment_count": 4, "views": 0, "votes": null }, { "id": 159761, "title": "Funny Stuff", "comment_count": 3, "views": 0, "votes": 10 }, { "id": 159865, "title": "What should I do when new features get better cv rmse but worse cv wrmsse", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 157769, "title": "Question: What is Magic?", "comment_count": 7, "views": 0, "votes": 10 }, { "id": 159145, "title": "Maybe weights in loss functions ...", "comment_count": 1, "views": 0, "votes": 5 }, { "id": 157830, "title": "Rules on teaming in Accuracy and Uncertainty", "comment_count": 4, "views": 0, "votes": 10 }, { "id": 160000, "title": "DIVIDE & PREDICT!", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 158762, "title": "Data from d_1913 to d_1941 be used for training?", "comment_count": 5, "views": 0, "votes": null }, { "id": 159107, "title": "Mean encoding", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 159034, "title": "M4 Competition Link", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 157370, "title": "What hardwares do you use?", "comment_count": 10, "views": 0, "votes": 3 }, { "id": 153963, "title": "Last post for M5", "comment_count": 21, "views": 0, "votes": 70 }, { "id": 155439, "title": "How to get your true public LB score & rank offline", "comment_count": 14, "views": 0, "votes": 86 }, { "id": 155566, "title": "I want to know how private LB is ranked", "comment_count": 6, "views": 0, "votes": 0 }, { "id": 158612, "title": "M5 Forecasting Encoder Decoder with Attention", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 158422, "title": "How did so many people achieve 0.0 MSE LOSS?", "comment_count": 2, "views": 0, "votes": null }, { "id": 154776, "title": "Moon Phase. Odd, yet helpful feature.", "comment_count": 16, "views": 0, "votes": 41 }, { "id": 157425, "title": "Questions about RMSE becoming 0.0", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 157171, "title": "Weather database", "comment_count": 5, "views": 0, "votes": null }, { "id": 155199, "title": "Thread to summarize all the neural network approaches", "comment_count": 5, "views": 0, "votes": 1 }, { "id": 158062, "title": "I think we should use Time Serie Split as CV strategy", "comment_count": 3, "views": 0, "votes": null }, { "id": 143070, "title": "WRMSSE custom objective function ", "comment_count": 41, "views": 0, "votes": 82 }, { "id": 156879, "title": "Ambiguity and Confusion Regarding Making Submission File for the Evaluation Stage", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 155460, "title": "Three downsides of submitting perfect Public submissions", "comment_count": 14, "views": 0, "votes": 27 }, { "id": 156915, "title": "Weighing the impact of weights", "comment_count": 0, "views": 0, "votes": 15 }, { "id": 157194, "title": "0.45863 public leader board", "comment_count": 3, "views": 0, "votes": null }, { "id": 156171, "title": "weights for evaluation period", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 154999, "title": "Be prepared for switch to private test set on June 1st", "comment_count": 5, "views": 0, "votes": 64 }, { "id": 147345, "title": "Prof Makridakis M Applied Forecasting course", "comment_count": 12, "views": 0, "votes": -23 }, { "id": 156802, "title": "Please Clarifily Submission format", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 156236, "title": "Kaggle notebook keeps running out of memory", "comment_count": 8, "views": 0, "votes": 4 }, { "id": 156770, "title": "Validation negatively affects Evaluation? Please clarify", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 137019, "title": "For those wondering about the intuition behind RMSSE score", "comment_count": 7, "views": 0, "votes": 34 }, { "id": 145520, "title": "Deep Learning LSTM Pytorch - My learning Kernel and resources ", "comment_count": 4, "views": 0, "votes": 22 }, { "id": 155770, "title": "Post-mortem analysis", "comment_count": 6, "views": 0, "votes": 18 }, { "id": 148505, "title": "Regression + Classification", "comment_count": 20, "views": 0, "votes": 45 }, { "id": 156031, "title": "Top-100 before leaderboard disaster", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 156214, "title": "Strange results of the rounding predicted values to true values", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 155452, "title": "Why is public LB still active?", "comment_count": 10, "views": 0, "votes": 7 }, { "id": 133652, "title": "Team merger submission limit", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 156095, "title": "Fine Tuning LightGBM from the Original Repo for reaching top", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 155557, "title": "Why this competition has gone stagnant?", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 156272, "title": "leaderboard with 0% errors? can we get some rules here?", "comment_count": 1, "views": 0, "votes": -4 }, { "id": 155427, "title": "Welcome to the \"Blackout\" Period", "comment_count": 3, "views": 0, "votes": 13 }, { "id": 155334, "title": "LightGBM Tweedie objective replication", "comment_count": 5, "views": 0, "votes": 3 }, { "id": 138228, "title": "Any ideas on Memory Saving?", "comment_count": 6, "views": 0, "votes": 5 }, { "id": 152767, "title": "Python NN Full Training Pipeline", "comment_count": 12, "views": 0, "votes": 36 }, { "id": 155920, "title": "CV with regard to the added evaluation data", "comment_count": 1, "views": 0, "votes": null }, { "id": 155906, "title": "Questions about the conpetiton", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 155891, "title": "How is zero score possible?", "comment_count": 1, "views": 0, "votes": null }, { "id": 155533, "title": "Directly replace prediction with true zero get worse score ?", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 155575, "title": "0 Score is now achieved", "comment_count": 3, "views": 0, "votes": null }, { "id": 155445, "title": "Validation forecasts in submission file", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 155332, "title": "Regarding Submission Time", "comment_count": 1, "views": 0, "votes": null }, { "id": 155691, "title": "Now some features are missing", "comment_count": 2, "views": 0, "votes": -1 }, { "id": 155751, "title": "You can still view your scores by submitting Validation file", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 155719, "title": "What are the days in submission dataset", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 155569, "title": "Validation Inclusion in the final score", "comment_count": 1, "views": 0, "votes": null }, { "id": 153728, "title": "I have a question about Leaderboard after 6.1", "comment_count": 12, "views": 0, "votes": 1 }, { "id": 149418, "title": "lightgbm.basic.LightGBMError: Cannot add validation data, since it has different bin mappers with training data", "comment_count": 1, "views": 0, "votes": 3 }, { "id": 155456, "title": "Final Score", "comment_count": 2, "views": 0, "votes": null }, { "id": 149754, "title": "How to avoid LightGBM memory spike when it starts training", "comment_count": 16, "views": 0, "votes": 53 }, { "id": 155242, "title": "What are we predicting ?", "comment_count": 2, "views": 0, "votes": null }, { "id": 143091, "title": "M4 Competition: 100k timeseries & 61 forecasting methods", "comment_count": 5, "views": 0, "votes": 15 }, { "id": 152270, "title": "How to get through 0.45", "comment_count": 13, "views": 0, "votes": 27 }, { "id": 142129, "title": "Best pure neural net model", "comment_count": 21, "views": 0, "votes": 22 }, { "id": 154472, "title": "Seq2Seq With Pytorch ", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 154499, "title": "Lightgbm - model approach advice", "comment_count": 4, "views": 0, "votes": null }, { "id": 151339, "title": "What do you mean by \"Recursive Features\" & \"day to day models\"?", "comment_count": 7, "views": 0, "votes": 9 }, { "id": 153502, "title": "Important point to consider in solving Time Series Forecasting", "comment_count": 5, "views": 0, "votes": 8 }, { "id": 139461, "title": "Multistep timeseries forecasting", "comment_count": 14, "views": 0, "votes": 37 }, { "id": 154411, "title": "frustration between catboost and lightgbm", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 154244, "title": "How to save memory with my decorator", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 154198, "title": "About Submissions After June 1st", "comment_count": 2, "views": 0, "votes": null }, { "id": 154343, "title": "memory issue about pd read function", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 151614, "title": "No Improvement From Day by Day Models", "comment_count": 19, "views": 0, "votes": 15 }, { "id": 154307, "title": "Pandas Multi-Indices for HTS, fast loading, etc.", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 152837, "title": "Lightgbm: Custom Loss Anything using PyTorch Autograd!", "comment_count": 3, "views": 0, "votes": 30 }, { "id": 153428, "title": "Further exploration: where to look ahead?", "comment_count": 9, "views": 0, "votes": 9 }, { "id": 153618, "title": "Different weight in WRMSSE for different horizions?", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 152170, "title": "Success with Neural Networks", "comment_count": 10, "views": 0, "votes": 9 }, { "id": 147090, "title": "Share your \"Magic\"", "comment_count": 44, "views": 0, "votes": 82 }, { "id": 153754, "title": "Sanity / Consistency Checks for M5 Forecasts", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 153281, "title": "One ARIMA per product", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 139974, "title": "Tidy the data!", "comment_count": 7, "views": 0, "votes": 8 }, { "id": 149657, "title": "WRMSSE volatility or loss function inadequacy ?", "comment_count": 4, "views": 0, "votes": 14 }, { "id": 153277, "title": "M5 for CatBoost", "comment_count": 2, "views": 0, "votes": null }, { "id": 133468, "title": "External Data/Pre-Trained Models Disclosure Thread", "comment_count": 68, "views": 0, "votes": 56 }, { "id": 152843, "title": "LSTM with item, date embeddings as features in Pytorch", "comment_count": 2, "views": 0, "votes": null }, { "id": 153386, "title": "It takes about 15 minutes to process 100 records.", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 153079, "title": "Question of Lightgbm", "comment_count": 3, "views": 0, "votes": null }, { "id": 153157, "title": "Confusion regarding after 1st June", "comment_count": 2, "views": 0, "votes": null }, { "id": 153213, "title": "Stable CV", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 151329, "title": "Model integration and blending", "comment_count": 43, "views": 0, "votes": 25 }, { "id": 151917, "title": "Some papers to start with", "comment_count": 1, "views": 0, "votes": 4 }, { "id": 152253, "title": "Time Series Transformations", "comment_count": 1, "views": 0, "votes": 7 }, { "id": 152829, "title": "Correlations among states product types", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 152709, "title": "Interpreting WRMSSE metric", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 148273, "title": "Speed-up LightGBM training", "comment_count": 20, "views": 0, "votes": 36 }, { "id": 152576, "title": "RMSSE caculation for validation dataset after 1st June ?", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 152384, "title": "does anyone using Lightgbm gpu version?", "comment_count": 4, "views": 0, "votes": null }, { "id": 148900, "title": "My Top 10 Notebooks of M5", "comment_count": 10, "views": 0, "votes": 27 }, { "id": 152408, "title": "Question about submission", "comment_count": 1, "views": 0, "votes": null }, { "id": 152148, "title": "Domain knowledge about events ", "comment_count": 2, "views": 0, "votes": 5 }, { "id": 137461, "title": "Top-down approaches", "comment_count": 6, "views": 0, "votes": 8 }, { "id": 152410, "title": "Looking for a team", "comment_count": 1, "views": 0, "votes": -5 }, { "id": 152051, "title": "Why \"fractional forecast\" is allowed? Does it have practical benefit to business?", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 152565, "title": "2016 is through February 29. leap year", "comment_count": 0, "views": 0, "votes": -3 }, { "id": 152225, "title": "Regression+classification models", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 152135, "title": "Catboost support tweedie now", "comment_count": 6, "views": 0, "votes": null }, { "id": 150593, "title": "A Friendly Reminder to Those Participating in M5 Competitions", "comment_count": 8, "views": 0, "votes": 23 }, { "id": 150078, "title": "Validation Sets and WRMSSE scoring on Benchmarks 1-5", "comment_count": 5, "views": 0, "votes": 25 }, { "id": 152117, "title": "LGBM/RF Training Time?? ", "comment_count": 2, "views": 0, "votes": -1 }, { "id": 152138, "title": "Host,plz?Promotion Info？", "comment_count": 3, "views": 0, "votes": null }, { "id": 149806, "title": "My method to select features", "comment_count": 27, "views": 0, "votes": 22 }, { "id": 149015, "title": "Corr btw target and lags, and multiprocess func", "comment_count": 6, "views": 0, "votes": 23 }, { "id": 147225, "title": "how do you work with outliers ?", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 142560, "title": "Convert rowed time into column", "comment_count": 2, "views": 0, "votes": null }, { "id": 151145, "title": "Estimated tweedie variance parameters for bottom level time series", "comment_count": 2, "views": 0, "votes": 14 }, { "id": 151263, "title": "Dark pipeline magic with luigi", "comment_count": 4, "views": 0, "votes": 4 }, { "id": 134044, "title": "RMSSE vs RMSE", "comment_count": 5, "views": 0, "votes": 11 }, { "id": 133467, "title": "Looking for a Team Megathread", "comment_count": 225, "views": 0, "votes": 26 }, { "id": 151399, "title": "Incorporating lags into keras lstm model", "comment_count": 4, "views": 0, "votes": null }, { "id": 151075, "title": "Huge shake?", "comment_count": 5, "views": 0, "votes": 5 }, { "id": 151101, "title": "Combining Kernels (State Space & LSTM)", "comment_count": 1, "views": 0, "votes": 4 }, { "id": 147656, "title": "One Single Regressor vs. Multiple Regressors for each product", "comment_count": 5, "views": 0, "votes": 1 }, { "id": 151197, "title": "Light GBM not working...Memory use error", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 150255, "title": "Compare \"apply\" and \"transform\" in pandas", "comment_count": 8, "views": 0, "votes": 9 }, { "id": 147961, "title": "Any \"time series\" model < 0.7?", "comment_count": 26, "views": 0, "votes": 6 }, { "id": 144576, "title": "Embeddings in seq2seq?", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 135341, "title": "Looking to form a team!", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 151332, "title": "Why is predicted sales such small number ?", "comment_count": 1, "views": 0, "votes": null }, { "id": 150955, "title": "Training store wise: State specific features", "comment_count": 7, "views": 0, "votes": null }, { "id": 151284, "title": "can't run my kernel", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 151242, "title": "Nan, infinity or large value error while checking the predictions", "comment_count": 1, "views": 0, "votes": null }, { "id": 150889, "title": "Submission file starts at a Saturday?", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 150675, "title": "Can we use RMSSE directly as loss function using NN model?", "comment_count": 4, "views": 0, "votes": null }, { "id": 150803, "title": "Notebook commit failure, but successful run on interactive session", "comment_count": 2, "views": 0, "votes": null }, { "id": 151288, "title": "HOLA", "comment_count": 0, "views": 0, "votes": -4 }, { "id": 150379, "title": "what if I submit more than 5 times per day?", "comment_count": 5, "views": 0, "votes": 0 }, { "id": 142833, "title": "BERT, transformer : moving from NLP to time series?", "comment_count": 26, "views": 0, "votes": 56 }, { "id": 150292, "title": "Some questions about Python Visualization", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 144307, "title": "Counting zeros in a rolling?", "comment_count": 7, "views": 0, "votes": 4 }, { "id": 150340, "title": "Does anyone met the probleme of data leakage?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 133614, "title": "SNAP: Supplemental Nutrition Assistance Program", "comment_count": 10, "views": 0, "votes": 44 }, { "id": 140919, "title": "Expressing Frustration: CV vs. LB", "comment_count": 74, "views": 0, "votes": 40 }, { "id": 139373, "title": "What are the Time series resources available for absolute beginners in Kaggle..?", "comment_count": 11, "views": 0, "votes": 27 }, { "id": 143077, "title": "my collection of ideas and tips", "comment_count": 4, "views": 0, "votes": 26 }, { "id": 149733, "title": "\"testing on unseen data\"", "comment_count": 2, "views": 0, "votes": null }, { "id": 149898, "title": "Submission error: CSV parsing error", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 149452, "title": "Data dualism or potential data leak", "comment_count": 2, "views": 0, "votes": 5 }, { "id": 148958, "title": "Overfit~! but where?", "comment_count": 8, "views": 0, "votes": null }, { "id": 149221, "title": "What is wm_yr_wk column?", "comment_count": 5, "views": 0, "votes": null }, { "id": 133657, "title": "GluonTS: Probabilistic time series modeling", "comment_count": 2, "views": 0, "votes": 23 }, { "id": 147425, "title": "Making prediction from simplest to complex", "comment_count": 4, "views": 0, "votes": 9 }, { "id": 148537, "title": "Better MAE but Worst result in leaderboard ", "comment_count": 4, "views": 0, "votes": null }, { "id": 149251, "title": "Can anyone please help me to kick start?", "comment_count": 4, "views": 0, "votes": -1 }, { "id": 141743, "title": "Some Worries About Overfitting", "comment_count": 18, "views": 0, "votes": 7 }, { "id": 149414, "title": "Everyday Low Price Policy", "comment_count": 0, "views": 0, "votes": -3 }, { "id": 144023, "title": "Beating 0.50 with an NN: Some tips", "comment_count": 26, "views": 0, "votes": 40 }, { "id": 149128, "title": "Correlations among time series of different stores/states", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 147733, "title": "Upcomming events as Features", "comment_count": 4, "views": 0, "votes": 5 }, { "id": 145011, "title": "Last digit of the price as a feature. Is it a sign of discount?", "comment_count": 5, "views": 0, "votes": 39 }, { "id": 144838, "title": "At least two types of patterns in the sales data", "comment_count": 1, "views": 0, "votes": 18 }, { "id": 148630, "title": "Any suggestion to use marketing model here?", "comment_count": 2, "views": 0, "votes": null }, { "id": 148412, "title": "What is mean of benchmark point?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 148204, "title": "LightGBM version 2.3.2 ", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 141092, "title": "Will this competition end under 0.4 ?", "comment_count": 18, "views": 0, "votes": 14 }, { "id": 148670, "title": "Time efficiency of WRMSSEEvaluator", "comment_count": 1, "views": 0, "votes": null }, { "id": 148702, "title": "Features for models", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 147659, "title": "Why are boosted trees so good for this competition?", "comment_count": 9, "views": 0, "votes": 4 }, { "id": 148264, "title": "Usage of this dataset for Master Thesis", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 136068, "title": "local RMSE/local WRMSSE/LB", "comment_count": 78, "views": 0, "votes": 64 }, { "id": 146435, "title": "Lag and Rolling of different combinations", "comment_count": 4, "views": 0, "votes": 1 }, { "id": 147438, "title": "Some confusion of cross validation", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 147946, "title": "Sample Submission: 60490 , Sales_Validation: 30480 ????", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 136035, "title": "Get a Date whether its Holiday or not; Useful in predicting sales.", "comment_count": 5, "views": 0, "votes": 9 }, { "id": 144027, "title": "should I consider other items' sales as features for a specific item?", "comment_count": 2, "views": 0, "votes": null }, { "id": 146828, "title": "Best Gradient Boosting (GB) model score", "comment_count": 5, "views": 0, "votes": 7 }, { "id": 147415, "title": "Thoughts on creating a good NN", "comment_count": 1, "views": 0, "votes": 5 }, { "id": 147924, "title": "Put your predictions into submission-format", "comment_count": 2, "views": 0, "votes": null }, { "id": 147892, "title": "Computation time difference: Colab and Kaggle", "comment_count": 1, "views": 0, "votes": null }, { "id": 147829, "title": "Looking for a teammate!", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 146958, "title": "what is the target variable in this data, I'm confused here when I see the submission file here, can any one help out?", "comment_count": 11, "views": 0, "votes": -7 }, { "id": 146258, "title": "Understanding differences between models", "comment_count": 3, "views": 0, "votes": 8 }, { "id": 147748, "title": "Plot unique number of ids", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 134712, "title": "Best Single Model", "comment_count": 28, "views": 0, "votes": 35 }, { "id": 147476, "title": "How to get an yearly trend for M5 - Accuracy data?", "comment_count": 2, "views": 0, "votes": -1 }, { "id": 147252, "title": "Memory issue on merging sales_train and sell_price datasets", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 145955, "title": "lightgbm memory spike at start of training", "comment_count": 8, "views": 0, "votes": 7 }, { "id": 137905, "title": "Statistical Benchmarks and WRMSSE", "comment_count": 13, "views": 0, "votes": 25 }, { "id": 146800, "title": "How to Start Tips/Guidance?", "comment_count": 7, "views": 0, "votes": 1 }, { "id": 147238, "title": "Need help applying trained model to make 30450 predictions", "comment_count": 2, "views": 0, "votes": -1 }, { "id": 141342, "title": "LGB categorical_feature setting", "comment_count": 9, "views": 0, "votes": 4 }, { "id": 147146, "title": "Evaluation metrics question ", "comment_count": 1, "views": 0, "votes": null }, { "id": 147077, "title": "Intel v.s. AMD", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 147017, "title": "I want to apply a cross validation but MLE", "comment_count": 3, "views": 0, "votes": null }, { "id": 146073, "title": " Differences between rmse in local and wrmsse in LB", "comment_count": 8, "views": 0, "votes": 3 }, { "id": 146684, "title": "Can you give any idea to forecast this time series?", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 134786, "title": "Is this a time series competition?", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 146784, "title": "Know which products are forecasted better", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 145064, "title": "Don't try many ideas at once!", "comment_count": 6, "views": 0, "votes": 15 }, { "id": 145767, "title": "LIGHTGBM parameter optimization", "comment_count": 7, "views": 0, "votes": 3 }, { "id": 145146, "title": "Kaggle Notebook - Commit", "comment_count": 2, "views": 0, "votes": null }, { "id": 146591, "title": "Ipwidgets After Commit", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 146665, "title": "Is there any event on 2011-12-25?", "comment_count": 2, "views": 0, "votes": -2 }, { "id": 145228, "title": "Weird price drops in single stores for single week. Errors?", "comment_count": 5, "views": 0, "votes": 17 }, { "id": 145889, "title": "Transforming the time series format (with local WRMSSE)", "comment_count": 0, "views": 0, "votes": 7 }, { "id": 146260, "title": "External Features", "comment_count": 2, "views": 0, "votes": null }, { "id": 144842, "title": "Holidays' calendars are different by state for ~10 days/year", "comment_count": 4, "views": 0, "votes": 22 }, { "id": 145716, "title": "in M5 Forecasting , why Accuracy one is more popular than Uncertainty?", "comment_count": 6, "views": 0, "votes": null }, { "id": 141715, "title": "Public Score 1.25463", "comment_count": 12, "views": 0, "votes": 2 }, { "id": 138679, "title": "Missing event start/end dates?", "comment_count": 1, "views": 0, "votes": 3 }, { "id": 144426, "title": "It's a Trap!", "comment_count": 3, "views": 0, "votes": 15 }, { "id": 144693, "title": "Lag variables for New Test Data", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 141150, "title": "M5想法交流", "comment_count": 26, "views": 0, "votes": -18 }, { "id": 133545, "title": "Here is an inspirational quote", "comment_count": 11, "views": 0, "votes": 14 }, { "id": 141515, "title": "Iterative Prediction Best Single Model to 0.5002", "comment_count": 12, "views": 0, "votes": 64 }, { "id": 144109, "title": "LighGBM weights as custom objective", "comment_count": 3, "views": 0, "votes": 2 }, { "id": 144473, "title": "Modelling closeness of major events", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 145002, "title": "Should the problem with new products be solved? ", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 144581, "title": "GPU gives worse results than CPU", "comment_count": 10, "views": 0, "votes": 1 }, { "id": 144440, "title": "Is the lightgbm better than time series models(such as lstm asnd GRU)", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 143873, "title": "Feature engineering: Days until X-mas", "comment_count": 5, "views": 0, "votes": 3 }, { "id": 144319, "title": "ARGONet: Time Series transformers", "comment_count": 1, "views": 0, "votes": 6 }, { "id": 144474, "title": " I'm just starting Kaggle and I don't know what is the right way to do it. Is it a good way to use a coefficient like \"alpha\"?", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 144243, "title": "LSTM modeling", "comment_count": 8, "views": 0, "votes": null }, { "id": 134392, "title": "Understand column wm_yr_wk", "comment_count": 7, "views": 0, "votes": 17 }, { "id": 142872, "title": "How Walmart Improves Forecast Accuracy with NVIDIA GPUs", "comment_count": 6, "views": 0, "votes": 18 }, { "id": 142656, "title": "Chapter 10 Forecasting hierarchical or grouped time series", "comment_count": 14, "views": 0, "votes": 7 }, { "id": 144446, "title": "Are there some suggestion about how to deal with time series forecast in lightgbm?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 144274, "title": "NA and Missing Values", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 144425, "title": "Dask lgbm?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 144410, "title": "Reduce memory usage further", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 143887, "title": "Hierarchy", "comment_count": 3, "views": 0, "votes": 4 }, { "id": 143751, "title": "How do you spot leakage?", "comment_count": 10, "views": 0, "votes": 2 }, { "id": 143639, "title": "How did you chose the best features", "comment_count": 6, "views": 0, "votes": 2 }, { "id": 143997, "title": "NotImplementedError: ix is not iterable", "comment_count": 9, "views": 0, "votes": -4 }, { "id": 143543, "title": "consumer behavior are sometimes hard to predict", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 143555, "title": "np.log1p(RMSE) vs RMSE vs LB", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 143655, "title": "M4 Competition winner - Using ES with RNNs for time series forecasting ", "comment_count": 0, "views": 0, "votes": 8 }, { "id": 143881, "title": "Resources for LGBM/gradient boosting/ tree based model", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 142947, "title": "Any one try for Encoder-Decoder Architecture ?", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 133476, "title": "Resources for Time Series Methods", "comment_count": 16, "views": 0, "votes": 40 }, { "id": 141852, "title": "Validation RMSE per target curve?", "comment_count": 7, "views": 0, "votes": 9 }, { "id": 143625, "title": "Study guide", "comment_count": 3, "views": 0, "votes": null }, { "id": 142940, "title": "Useful and Useless Features", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 143295, "title": "Does magic multipliers (1.02 - 1.04) violate the competition rules?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 143200, "title": "Understanding the Walmart ", "comment_count": 3, "views": 0, "votes": 4 }, { "id": 143728, "title": "First ML attempt with random search", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 143063, "title": "Outliers detected in prices", "comment_count": 0, "views": 0, "votes": 18 }, { "id": 143510, "title": "Why is this code not running? Please help me", "comment_count": 1, "views": 0, "votes": null }, { "id": 143767, "title": "What do we need to predict/do", "comment_count": 1, "views": 0, "votes": -2 }, { "id": 143197, "title": "Is this Kernel or non-Kernel competition?", "comment_count": 6, "views": 0, "votes": 1 }, { "id": 143415, "title": "Transformer starter kernel", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 143623, "title": "Benchmark Models - Usage & Evaluation", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 143621, "title": "the term of the training data", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 143263, "title": "Question about the dataset", "comment_count": 2, "views": 0, "votes": 0 }, { "id": 143123, "title": "fake public kernel", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 142923, "title": "Fighting zeros - let's share strategies", "comment_count": 0, "views": 0, "votes": 15 }, { "id": 140424, "title": "Generating all 42840 Series", "comment_count": 2, "views": 0, "votes": 9 }, { "id": 142425, "title": "[Requests] Notebook Publish", "comment_count": 7, "views": 0, "votes": 7 }, { "id": 142669, "title": "Dealing with lots of 0s?", "comment_count": 4, "views": 0, "votes": 4 }, { "id": 142770, "title": "magic multiplier", "comment_count": 5, "views": 0, "votes": 1 }, { "id": 141302, "title": "Ideas that really work (or not) for this competition", "comment_count": 9, "views": 0, "votes": 36 }, { "id": 142991, "title": "extra column on submission", "comment_count": 2, "views": 0, "votes": null }, { "id": 142390, "title": "Why only 1 submission?", "comment_count": 8, "views": 0, "votes": 5 }, { "id": 142948, "title": "Kaggle notebook use problems", "comment_count": 1, "views": 0, "votes": null }, { "id": 142536, "title": "How to compute RMSSE when actual values are all zeros?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 142671, "title": "New Features Generated", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 135626, "title": "Does anyone have successful NN?", "comment_count": 8, "views": 0, "votes": 8 }, { "id": 141942, "title": "Obligatory best single model score", "comment_count": 17, "views": 0, "votes": 2 }, { "id": 133582, "title": "Running out of RAM...", "comment_count": 22, "views": 0, "votes": 8 }, { "id": 140600, "title": "Please make good Python starters kernel", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 142621, "title": "Can't see my previous notebook.", "comment_count": 1, "views": 0, "votes": null }, { "id": 139474, "title": "Why R Performing Better than Python ?", "comment_count": 15, "views": 0, "votes": 13 }, { "id": 141557, "title": "How to use weights correctly", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 142488, "title": "Rounding before metric calculation", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 142294, "title": "How to avoid overfitting to public LB?", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 141682, "title": "RMSSE calculation: leading vs. inner no-sales periods", "comment_count": 6, "views": 0, "votes": 5 }, { "id": 141602, "title": "From point to uncertainty prediction", "comment_count": 3, "views": 0, "votes": 16 }, { "id": 141270, "title": "A shiny dashboard for M5 forecast competition", "comment_count": 0, "views": 0, "votes": 17 }, { "id": 142271, "title": "Where are the sell_train records for the ids ending in evaluation", "comment_count": 1, "views": 0, "votes": -1 }, { "id": 141656, "title": "Number of M5 series per aggregation level", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 142225, "title": "Score Based only on validation?", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 142108, "title": "Join datasets with tf.data", "comment_count": 1, "views": 0, "votes": null }, { "id": 142210, "title": "Final Submissions and Test Submissions", "comment_count": 2, "views": 0, "votes": null }, { "id": 138085, "title": "Intermittent Demand vs. Large 0 Gaps", "comment_count": 12, "views": 0, "votes": 40 }, { "id": 142055, "title": "How are people using the hierarchical nature of the data?", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 142343, "title": "May I send a Job Description here?", "comment_count": 1, "views": 0, "votes": -3 }, { "id": 140206, "title": "Some insights", "comment_count": 8, "views": 0, "votes": 20 }, { "id": 141197, "title": "Why does Poisson objective perform worse than RMSE?", "comment_count": 3, "views": 0, "votes": 2 }, { "id": 141797, "title": "seq2seq approch", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 141595, "title": "How can I prevent the notebook from crashing?", "comment_count": 5, "views": 0, "votes": 0 }, { "id": 140781, "title": "Modern Methods vs Classic Time Series", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 141765, "title": "Download problem", "comment_count": 12, "views": 0, "votes": null }, { "id": 141118, "title": "Submission File ", "comment_count": 3, "views": 0, "votes": 6 }, { "id": 140921, "title": "RAM Problem", "comment_count": 7, "views": 0, "votes": 2 }, { "id": 140371, "title": "Metric for the beginners", "comment_count": 2, "views": 0, "votes": null }, { "id": 139769, "title": "Does ARIMA takes care of non-stationarity by itself?", "comment_count": 6, "views": 0, "votes": 2 }, { "id": 135358, "title": "Guidelines PDF?", "comment_count": 15, "views": 0, "votes": 6 }, { "id": 133912, "title": "Could Prophet do the magic? Docs + Fine Tuning", "comment_count": 3, "views": 0, "votes": 5 }, { "id": 140955, "title": "Iterative Incremental Learning big dataset", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 140965, "title": "Submission rules", "comment_count": 2, "views": 0, "votes": null }, { "id": 140290, "title": "Difficulty in handling Data after merging.", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 140512, "title": "Why rounding the prediction worsen the LB score? ", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 138882, "title": "Thresholds for converting to int", "comment_count": 12, "views": 0, "votes": 3 }, { "id": 140535, "title": "Days 1914 ++", "comment_count": 4, "views": 0, "votes": null }, { "id": 140418, "title": "evaluation csv file not found", "comment_count": 3, "views": 0, "votes": null }, { "id": 140130, "title": "First time in the gold zone", "comment_count": 3, "views": 0, "votes": 5 }, { "id": 140335, "title": "Number of rows differ", "comment_count": 2, "views": 0, "votes": null }, { "id": 138268, "title": "sell_price Nan means no sales ", "comment_count": 13, "views": 0, "votes": 17 }, { "id": 140111, "title": "Is there a lookup table for product ID vs description?", "comment_count": 2, "views": 0, "votes": null }, { "id": 134244, "title": "RMSSE Weights - please clarify", "comment_count": 11, "views": 0, "votes": 24 }, { "id": 138878, "title": "How to speed up the process of feature selection/feature engineering?", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 139494, "title": "Question about decimal demand forecast", "comment_count": 2, "views": 0, "votes": null }, { "id": 138652, "title": "Does GPU improve LightGBM execution time?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 139066, "title": "Objective function for WRMSSE?", "comment_count": 3, "views": 0, "votes": 4 }, { "id": 139300, "title": "Looking for a teammate", "comment_count": 1, "views": 0, "votes": -2 }, { "id": 139460, "title": "Are d_1914 to d_1941 sales available already?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 139234, "title": "Top down forecast distribution", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 135896, "title": "Do you use 27_500_000 rows of training set?", "comment_count": 5, "views": 0, "votes": 7 }, { "id": 138113, "title": "Decimal demand forecast ", "comment_count": 5, "views": 0, "votes": 5 }, { "id": 139161, "title": "Predicting d_1914 to d_1941", "comment_count": 2, "views": 0, "votes": null }, { "id": 139019, "title": "Is the public lgb kernel using future data?", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 138803, "title": "Store the selling price of an item in a store in a particular wm_yr_wk in a json file (or dict)", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 138951, "title": "New to ML - Can output be a matrix?", "comment_count": 2, "views": 0, "votes": null }, { "id": 138031, "title": "Holt Winters gives negative values", "comment_count": 6, "views": 0, "votes": 3 }, { "id": 138779, "title": "New Neural network forecasting : mlmodels", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 138195, "title": "R vs Python?", "comment_count": 10, "views": 0, "votes": 1 }, { "id": 139003, "title": "Notebook crashes because of Lightgbm", "comment_count": 1, "views": 0, "votes": null }, { "id": 137580, "title": "How can I get larger graphs in R Notebook?", "comment_count": 6, "views": 0, "votes": 1 }, { "id": 138320, "title": "Why are some of the events not recorded?", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 138132, "title": "To Admin: question about AMLT team", "comment_count": 6, "views": 0, "votes": 2 }, { "id": 137492, "title": "WRMSSE Evaluation Dashboard", "comment_count": 0, "views": 0, "votes": 24 }, { "id": 134032, "title": "Data Description", "comment_count": 4, "views": 0, "votes": 17 }, { "id": 138568, "title": "How do you find an overfit?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 138240, "title": "FOODS FE", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 137217, "title": "Negative value", "comment_count": 6, "views": 0, "votes": 7 }, { "id": 137851, "title": "Regression Models", "comment_count": 1, "views": 0, "votes": null }, { "id": 134088, "title": "How to determine CV?", "comment_count": 6, "views": 0, "votes": 7 }, { "id": 137909, "title": "Comparisons of a couple intuitive forecasts", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 137710, "title": "M5 Competition", "comment_count": 1, "views": 0, "votes": null }, { "id": 135537, "title": "Getting started ", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 134315, "title": "Evaluation metric", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 137809, "title": "Error in Data Processing: Kernel Died While Waiting For Execute Reply", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 134072, "title": "RMSSE metric question", "comment_count": 8, "views": 0, "votes": 31 }, { "id": 136038, "title": "submission rmse very high 2.xxxxx", "comment_count": 5, "views": 0, "votes": 3 }, { "id": 136993, "title": "Running out of memory. Need serious help.", "comment_count": 7, "views": 0, "votes": 4 }, { "id": 134603, "title": "Submission file forecast horizon", "comment_count": 5, "views": 0, "votes": 8 }, { "id": 135883, "title": "What's snap_CA? ", "comment_count": 4, "views": 0, "votes": 9 }, { "id": 137026, "title": "Denominator of RMSSE", "comment_count": 4, "views": 0, "votes": 2 }, { "id": 136130, "title": "How to arrange features ?", "comment_count": 6, "views": 0, "votes": null }, { "id": 136036, "title": "Effective Reduction in Memory (445MB to 57MB) of sales_train_validation Dataset", "comment_count": 6, "views": 0, "votes": 3 }, { "id": 137284, "title": "Number of sales days in dataset?", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 137420, "title": "M5 repository with benchmark methods", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 135252, "title": "Prices for the future", "comment_count": 5, "views": 0, "votes": 14 }, { "id": 135553, "title": "Python Benmark Models in Github", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 135388, "title": "Saving Memory on the sales_train_validation data", "comment_count": 8, "views": 0, "votes": 11 }, { "id": 135620, "title": "This comp is going to get crowded...", "comment_count": 5, "views": 0, "votes": 18 }, { "id": 135950, "title": "An R data package M5comp for M5 competition", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 135981, "title": "How to drastically speed up rolling windows computations?", "comment_count": 3, "views": 0, "votes": null }, { "id": 135417, "title": "Five minutes to make a submission? ", "comment_count": 10, "views": 0, "votes": 2 }, { "id": 135895, "title": "Memory Error (kernel restarting)", "comment_count": 4, "views": 0, "votes": 3 }, { "id": 134106, "title": "YouTube Tutotial", "comment_count": 3, "views": 0, "votes": 11 }, { "id": 136831, "title": "Quick Memory reduction than reduce_memory_usage", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 135709, "title": "Simple Linear Regression or LGBM or XG Boost fitting goes our of Memory", "comment_count": 1, "views": 0, "votes": 4 }, { "id": 134938, "title": "reducing run time", "comment_count": 2, "views": 0, "votes": 2 }, { "id": 136023, "title": "Reduce the Memory Size of the Dataset by ~70%", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 135833, "title": "Does anyone know how to link github and kaggle together？", "comment_count": 2, "views": 0, "votes": null }, { "id": 134683, "title": "Freeing notebook memory", "comment_count": 5, "views": 0, "votes": 7 }, { "id": 135846, "title": "Unable to view my own notebooks", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 135390, "title": "How would epidemics, such as COVID-19, impact forecasts?", "comment_count": 3, "views": 0, "votes": -1 }, { "id": 135803, "title": "Beginner looking for resources", "comment_count": 2, "views": 0, "votes": null }, { "id": 135669, "title": "Type of Models to be built: Cost vs Efficiency", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 134560, "title": "Time series clustering/classification and different models for different cluster/class of time series", "comment_count": 2, "views": 0, "votes": 4 }, { "id": 135781, "title": "Implementing the Evaluation Metrics", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 133688, "title": "Submission file", "comment_count": 3, "views": 0, "votes": 2 }, { "id": 135089, "title": "Train model in another machine?", "comment_count": 6, "views": 0, "votes": 4 }, { "id": 135652, "title": "GOOD", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 135752, "title": "Dimensionality reduction", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 133939, "title": "There will be a rescore soon", "comment_count": 25, "views": 0, "votes": 33 }, { "id": 134556, "title": "What is the mean of 'snap' in columns?", "comment_count": 3, "views": 0, "votes": 10 }, { "id": 134667, "title": "EDIT: Rescore Complete", "comment_count": 13, "views": 0, "votes": 12 }, { "id": 135297, "title": "Test", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 134972, "title": "What/Who is \"xxx.csv\" in Leaderboard?", "comment_count": 5, "views": 0, "votes": 2 }, { "id": 134069, "title": "Visual Explanations of the Datasets", "comment_count": 16, "views": 0, "votes": 29 }, { "id": 135279, "title": "Daily values", "comment_count": 1, "views": 0, "votes": 2 }, { "id": 135238, "title": "Submitting doesn't make much sense?..", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 134599, "title": "sample submission date range", "comment_count": 5, "views": 0, "votes": 5 }, { "id": 134915, "title": "Student Team Prize Eligibility Criteria", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 134777, "title": "Question about framework in Public kernel.", "comment_count": 4, "views": 0, "votes": 6 }, { "id": 133823, "title": "FBProphet first approach", "comment_count": 4, "views": 0, "votes": 6 }, { "id": 135047, "title": "M5 Uncertainty - Now Open for Submissions", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 134910, "title": "Getting Started with M5 Forecasting by Understanding Data", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 134796, "title": "source code M4 Competition", "comment_count": 0, "views": 0, "votes": 7 }, { "id": 133904, "title": "Validation strategies", "comment_count": 6, "views": 0, "votes": 25 }, { "id": 133649, "title": "Empty github?", "comment_count": 9, "views": 0, "votes": 14 }, { "id": 134779, "title": "Definition of AMLT?", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 134337, "title": "What steps would you take to run the M4 competition winning program?", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 134794, "title": "GitHub Action to push Kaggle kernel", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 134292, "title": "question about sell_prices", "comment_count": 1, "views": 0, "votes": 7 }, { "id": 134132, "title": "5 days in, already cheaters", "comment_count": 9, "views": 0, "votes": 10 }, { "id": 133576, "title": "Evaluation row don't effect LB", "comment_count": 5, "views": 0, "votes": 4 }, { "id": 134361, "title": "Zero Sales", "comment_count": 3, "views": 0, "votes": 5 }, { "id": 134490, "title": "This data is annoying! So I wrangled it...", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 134698, "title": "Submission error - stuck at Almost Ready", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 134440, "title": "Validation Struggles...", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 134298, "title": "guys, do you find that zero observations are extremely high ? ", "comment_count": 3, "views": 0, "votes": null }, { "id": 133622, "title": "Kaggle: Time series forecasting challenges", "comment_count": 2, "views": 0, "votes": 18 }, { "id": 133644, "title": "Time Series with Intermittent Demand", "comment_count": 2, "views": 0, "votes": 18 }, { "id": 133787, "title": "Confused by number of products", "comment_count": 2, "views": 0, "votes": 6 }, { "id": 133498, "title": "Submission file for point forecast does not contain aggregates", "comment_count": 9, "views": 0, "votes": 9 }, { "id": 133968, "title": "Missing Columns in \"sales_train_validation.csv\"", "comment_count": 3, "views": 0, "votes": 3 }, { "id": 134281, "title": "Help! submission error", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 133842, "title": "Teams/rules/sharing/risk... how will it work?", "comment_count": 1, "views": 0, "votes": 9 }, { "id": 134242, "title": "Where to start?", "comment_count": 1, "views": 0, "votes": null }, { "id": 134007, "title": "M5 Competition : EDA + Models", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 133714, "title": "CV or Holdout VS LB", "comment_count": 2, "views": 0, "votes": 3 }, { "id": 133536, "title": "Paper : Learnings from Kaggle’s Forecasting Competitions", "comment_count": 0, "views": 0, "votes": 13 }, { "id": 133537, "title": "awesome-time-series", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 133679, "title": "Baseline forecasting methods, don't underestimate!", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 133531, "title": "Winning Solutions & Data For M4 Competition", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 133544, "title": "Free Prediction Market for Student Team", "comment_count": 0, "views": 0, "votes": 1 } ], "errors": [] }