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      "ref": "tomcwalker/keras-nn-with-custom-loss-function-for-gini-auc",
      "title": "Keras NN with custom loss  function for Gini/AUC",
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      "kernel_id": "437820"
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      "ref": "alexfir/expected-gini-standard-error",
      "title": "Expected gini standard error ",
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      "kernel_id": "437566"
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      "ref": "vpaslay/is-your-small-gini-significant",
      "title": "Is Your Small Gini Significant?",
      "source": "live",
      "kernel_id": "437393"
    },
    {
      "ref": "aharless/stacker-with-oof-output",
      "title": "Stacker with OOF Output",
      "source": "live",
      "kernel_id": "437359"
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      "ref": "asindico/why-such-a-low-score-with-nn",
      "title": "Why such a low score with NN ?",
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      "kernel_id": "437287"
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    {
      "ref": "aharless/cv-for-keui-shen-nong-s-pascal-forza-model",
      "title": "CV for Keui Shen Nong's Pascal/Forza Model",
      "source": "live",
      "kernel_id": "437270"
    },
    {
      "ref": "chiranjeevivegi/xgboost-0-285-customlabel-weight-fillna-median",
      "title": "XGBoost(0.285) Customlabel weight & fillna: median",
      "source": "live",
      "kernel_id": "436520"
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    {
      "ref": "alexfir/target-encoding-using-variance",
      "title": "Target encoding using variance",
      "source": "live",
      "kernel_id": "435842"
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    {
      "ref": "loveall/forza-baseline-ssk",
      "title": "Forza Baseline_ssk",
      "source": "live",
      "kernel_id": "435764"
    },
    {
      "ref": "xbf6xbf/single-xgb-lb284",
      "title": "single xgb lb284",
      "source": "live",
      "kernel_id": "435749"
    },
    {
      "ref": "loveall/forza-baseline-g0kagglers",
      "title": "Forza Baseline_G0Kagglers",
      "source": "live",
      "kernel_id": "435028"
    },
    {
      "ref": "mathcass/tips-for-using-scikit-learn-for-evaluation",
      "title": "Tips for Using Scikit-Learn for Evaluation",
      "source": "live",
      "kernel_id": "435004"
    },
    {
      "ref": "loveall/entity-embedding-neural-net-gokagglers",
      "title": "Entity Embedding Neural Net_GoKagglers",
      "source": "live",
      "kernel_id": "434964"
    },
    {
      "ref": "loveall/rgf-with-10-newfeatures-gokagglers",
      "title": "RGF with 10 newfeatures_GoKagglers",
      "source": "live",
      "kernel_id": "434893"
    },
    {
      "ref": "claudiovalim/lb-0-287-porto-seguro-mix",
      "title": "LB 0.287 - Porto Seguro Mix",
      "source": "live",
      "kernel_id": "434889"
    },
    {
      "ref": "loveall/lb-0-287-porto-seguro-mix-gokagglers",
      "title": "LB 0.287 - Porto Seguro Mix_GoKagglers",
      "source": "live",
      "kernel_id": "434885"
    },
    {
      "ref": "loveall/forza-baseline",
      "title": "Forza Baseline",
      "source": "live",
      "kernel_id": "434870"
    },
    {
      "ref": "loveall/victor-s-mix-with-logits-gokagglers",
      "title": "Victor's Mix with Logits_GoKagglers",
      "source": "live",
      "kernel_id": "434850"
    },
    {
      "ref": "aharless/playing-with-joe-eddy-s-nn",
      "title": "Playing with Joe Eddy's NN",
      "source": "live",
      "kernel_id": "434694"
    },
    {
      "ref": "loveall/forza-baseline-gokagglers",
      "title": "Forza Baseline_GoKagglers",
      "source": "live",
      "kernel_id": "434484"
    },
    {
      "ref": "priyasd/predictive-modelling-using-forest",
      "title": "Predictive modelling using Forest",
      "source": "live",
      "kernel_id": "434225"
    },
    {
      "ref": "loveall/victor-s-mix-with-logits-instead-of-ranks",
      "title": "Victor's Mix with Logits Instead of Ranks",
      "source": "live",
      "kernel_id": "434067"
    },
    {
      "ref": "aharless/victor-s-mix-with-logits-now-regularized",
      "title": "Victor's Mix with Logits (now Regularized)",
      "source": "live",
      "kernel_id": "433859"
    },
    {
      "ref": "aquatic/entity-embedding-neural-net",
      "title": "Entity Embedding Neural Net",
      "source": "live",
      "kernel_id": "433757"
    },
    {
      "ref": "vpaslay/lb-0-287-porto-seguro-mix",
      "title": "LB 0.287 - Porto Seguro Mix",
      "source": "live",
      "kernel_id": "433187"
    },
    {
      "ref": "isaienkov/lb-0-286-with-addition-of-nn-ensemble",
      "title": "LB 0.286 with  addition of NN ensemble",
      "source": "live",
      "kernel_id": "433113"
    },
    {
      "ref": "vmathur/porto-seguro-eda",
      "title": "Porto Seguro EDA",
      "source": "live",
      "kernel_id": "432996"
    },
    {
      "ref": "serigne/lb-0-286-with-harmonic-mean",
      "title": "LB 0.286 with Harmonic mean",
      "source": "live",
      "kernel_id": "432837"
    },
    {
      "ref": "nguyenhnguyen/notebook030007e986",
      "title": "Notebook030007e986",
      "source": "live",
      "kernel_id": "432504"
    },
    {
      "ref": "aharless/dude-that-s-so-deep",
      "title": "Dude, that's so deep...",
      "source": "live",
      "kernel_id": "432305"
    },
    {
      "ref": "tunguz/lb-0-286-with-submission-file",
      "title": "LB 0.286 with submission file",
      "source": "live",
      "kernel_id": "432293"
    },
    {
      "ref": "loveall/base-on-single-xgb-lb-0-284-gokagglers",
      "title": "Base on  single XGB LB(0.284)_GoKagglers",
      "source": "live",
      "kernel_id": "432116"
    },
    {
      "ref": "loveall/lb-0-286-from-4-public-kernals-gokagglers",
      "title": "LB 0.286 from 4 public kernals_GoKagglers",
      "source": "live",
      "kernel_id": "431930"
    },
    {
      "ref": "loveall/rgf-target-encoding-upsampling",
      "title": "RGF + Target Encoding + Upsampling",
      "source": "live",
      "kernel_id": "431665"
    },
    {
      "ref": "beletecheneke/lb-0-286-from-four-public-kernals-submission-files",
      "title": "LB 0.286 from four public kernals submission files",
      "source": "live",
      "kernel_id": "431542"
    },
    {
      "ref": "yl1202/5-layers-mlp-classifier-0272",
      "title": "5_layers_MLP_classifier_0272",
      "source": "live",
      "kernel_id": "431490"
    },
    {
      "ref": "tunguz/rgf-target-encoding-0-282-on-lb",
      "title": "RGF + Target Encoding + Upsampling",
      "source": "live",
      "kernel_id": "431138"
    },
    {
      "ref": "isaienkov/1d-convolutional-neural-network-starter",
      "title": "1D convolutional neural network starter",
      "source": "live",
      "kernel_id": "430944"
    },
    {
      "ref": "sudhirnl7/xgboost-with-stratifiedkflod-lb-0-282",
      "title": "XGBoost with StratifiedKFlod LB(0.282)",
      "source": "live",
      "kernel_id": "430811"
    },
    {
      "ref": "loveall/0-285-lb-average-of-3xgboost-lightgbm-nn",
      "title": "0.285(LB) - Average of (3XGBoost, LightGBM, NN)",
      "source": "live",
      "kernel_id": "430635"
    },
    {
      "ref": "pluchme/0-285-lb-average-of-3xgboost-lightgbm-nn",
      "title": "0.285(LB) - Average of 3XGBoost, LightGBM, NN",
      "source": "live",
      "kernel_id": "429971"
    },
    {
      "ref": "plnimmi/data-analysis-and-summary-report",
      "title": "Data Analysis and Summary Report",
      "source": "live",
      "kernel_id": "429932"
    },
    {
      "ref": "rafjaa/resampling-strategies-for-imbalanced-datasets",
      "title": "Resampling strategies for imbalanced datasets",
      "source": "live",
      "kernel_id": "429852"
    },
    {
      "ref": "elikplim/xgboost-vs-ann-with-swish",
      "title": "XGBoost vs ANN(with Swish) ",
      "source": "live",
      "kernel_id": "429188"
    },
    {
      "ref": "briwill/safe-driver-eda-and-preliminary-feature-selection",
      "title": "Safe Driver EDA and Preliminary Feature Selection",
      "source": "live",
      "kernel_id": "428773"
    },
    {
      "ref": "scirpus/regularized-greedy-forest",
      "title": "Regularized Greedy Forest",
      "source": "live",
      "kernel_id": "428087"
    },
    {
      "ref": "arthurlpgc/lgbm-ensemble-try-17-on-porto-seguro",
      "title": "LGBM Ensemble Try #17 on Porto Seguro",
      "source": "live",
      "kernel_id": "427745"
    },
    {
      "ref": "chiranjeevivegi/random-forest-starter-code-0-265",
      "title": "Random Forest Starter Code (0.265)",
      "source": "live",
      "kernel_id": "427572"
    },
    {
      "ref": "arthurlpgc/emsemble-try-16-on-porto-seguro",
      "title": "Emsemble Try #16 on Porto Seguro",
      "source": "live",
      "kernel_id": "427464"
    },
    {
      "ref": "bssasikanth/xgboost",
      "title": "xgboost",
      "source": "live",
      "kernel_id": "427198"
    },
    {
      "ref": "ogrellier/can-early-stopping-generalize",
      "title": "can early stopping generalize?",
      "source": "live",
      "kernel_id": "426632"
    },
    {
      "ref": "smitashinde/prediction-for-porto-seguro-s-safe-driver",
      "title": "Prediction for porto Seguro’s Safe Driver ",
      "source": "live",
      "kernel_id": "426557"
    },
    {
      "ref": "scirpus/libffm-generator-lb-280",
      "title": "LibFFM Generator (LB .280)",
      "source": "live",
      "kernel_id": "426468"
    },
    {
      "ref": "tekrei/apache-spark-gbtclassifier-with-cv",
      "title": "Apache Spark GBTClassifier with CV",
      "source": "live",
      "kernel_id": "425658"
    },
    {
      "ref": "bisgsingh/data-exploration-and-feature-selection",
      "title": "Data Exploration and feature selection ",
      "source": "live",
      "kernel_id": "425599"
    },
    {
      "ref": "scirpus/clustering-on-just-missing-categories",
      "title": "Clustering on just missing categories",
      "source": "live",
      "kernel_id": "425404"
    },
    {
      "ref": "danieleewww/stacking-lb-0-285",
      "title": "Stacking - LB 0.285",
      "source": "live",
      "kernel_id": "423748"
    },
    {
      "ref": "danieleewww/simple-stacker-lb-0-284",
      "title": "Simple Stacker LB 0.284",
      "source": "live",
      "kernel_id": "423636"
    },
    {
      "ref": "areeves87/aggregate-20-kernel-csvs-by-median-rank-lb-285",
      "title": "Aggregate 20 kernel csvs by median rank - LB .285",
      "source": "live",
      "kernel_id": "423543"
    },
    {
      "ref": "davibarreira/porto-seguro-a-bit-of-data-exploration",
      "title": "Porto Seguro - A bit of data exploration",
      "source": "live",
      "kernel_id": "423255"
    },
    {
      "ref": "osciiart/porto-seguro-the-essential-kickstarter",
      "title": "Porto Seguro: The Essential Kickstarter",
      "source": "live",
      "kernel_id": "422985"
    },
    {
      "ref": "fabiendaniel/set-optimal-weights-in-model-averaging-lb-0-283",
      "title": "Set optimal weights in model averaging [LB: 0.283]",
      "source": "live",
      "kernel_id": "422913"
    },
    {
      "ref": "ogrellier/parameter-tuning-5-x-2-fold-cv-statistical-test",
      "title": "Parameter tuning : 5 x 2-fold CV statistical test",
      "source": "live",
      "kernel_id": "422864"
    },
    {
      "ref": "danieleewww/xgboost-k-fold-with-log-odds-aggregation",
      "title": "XGBoost K-fold with Log-Odds Aggregation",
      "source": "live",
      "kernel_id": "422430"
    },
    {
      "ref": "chongyu/selection-of-cat-by-hypothesis",
      "title": "Selection of _cat by Hypothesis",
      "source": "live",
      "kernel_id": "422418"
    },
    {
      "ref": "chongyu/selection-of-cat-based-on-hypothesis",
      "title": "Selection of _cat based on Hypothesis",
      "source": "live",
      "kernel_id": "422353"
    },
    {
      "ref": "danieleewww/logistic-of-genetic-features",
      "title": "Logistic of Genetic Features",
      "source": "live",
      "kernel_id": "422293"
    },
    {
      "ref": "chongyu/notebook12ffcc1f08",
      "title": "Notebook12ffcc1f08",
      "source": "live",
      "kernel_id": "422271"
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    {
      "ref": "yl1202/which-gini-is-correct",
      "title": "which_gini_is_correct",
      "source": "live",
      "kernel_id": "422153"
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    {
      "ref": "aharless/logistic-of-genetic-features",
      "title": "Logistic of Genetic Features",
      "source": "live",
      "kernel_id": "422034"
    },
    {
      "ref": "madsonrda/porto-seguro-competition-analysis",
      "title": "Porto Seguro competition' Analysis",
      "source": "live",
      "kernel_id": "421687"
    },
    {
      "ref": "romainloiseau/notebook2c7adcf8e2",
      "title": "Notebook2c7adcf8e2",
      "source": "live",
      "kernel_id": "421613"
    },
    {
      "ref": "danieleewww/new-features-xgb-upsampling-bayesopt",
      "title": "New features, XGB upsampling + BayesOpt",
      "source": "live",
      "kernel_id": "421527"
    },
    {
      "ref": "chechir/simple-analysis-on-categorical-variables",
      "title": "Simple analysis on categorical variables",
      "source": "live",
      "kernel_id": "421456"
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    {
      "ref": "devm2024/feature-construction-using-autoencoder-tf",
      "title": "Feature construction using Autoencoder(TF)",
      "source": "live",
      "kernel_id": "420991"
    },
    {
      "ref": "mrinalni/data-visualization",
      "title": "Data Visualization ",
      "source": "live",
      "kernel_id": "420849"
    },
    {
      "ref": "faizalabdkadir/porto-seguro-visual-eda",
      "title": "Porto Seguro Visual EDA",
      "source": "live",
      "kernel_id": "420837"
    },
    {
      "ref": "aharless/rgf-or-xgb-k-fold-with-log-odds-averaging",
      "title": "RGF or XGB, K-fold with Log-Odds Averaging",
      "source": "live",
      "kernel_id": "420551"
    },
    {
      "ref": "darkredhorse/safe-driver-prediction-ann",
      "title": "Safe Driver Prediction ANN",
      "source": "live",
      "kernel_id": "420270"
    },
    {
      "ref": "aaronlang/gini-index-s-step-by-step-visualization",
      "title": "Gini Index's step by step visualization",
      "source": "live",
      "kernel_id": "420077"
    },
    {
      "ref": "vaibhao/porto-seguro-s-safe-driver-prediction-part-2",
      "title": "Porto Seguro’s Safe Driver Prediction part 2",
      "source": "live",
      "kernel_id": "420048"
    },
    {
      "ref": "suchravi/python-data-preprocessing",
      "title": "PYTHON DATA PREPROCESSING",
      "source": "live",
      "kernel_id": "419557"
    },
    {
      "ref": "aquatic/shallow-keras-nn-with-upsampling-27-lb",
      "title": "Shallow Keras NN With Upsampling .27+ LB ",
      "source": "live",
      "kernel_id": "419379"
    },
    {
      "ref": "tilii7/new-features-xgb-upsampling-bayesopt",
      "title": "New features, XGB upsampling + BayesOpt",
      "source": "live",
      "kernel_id": "419280"
    },
    {
      "ref": "loveall/lgb-esemble-xgb-be-in-top-100-with-lb-0-285",
      "title": "Lgb Esemble + Xgb - Be in Top 100 with LB 0.285",
      "source": "live",
      "kernel_id": "419170"
    },
    {
      "ref": "asindico/porto-seguro-feature-analysis",
      "title": "Porto Seguro Feature Analysis",
      "source": "live",
      "kernel_id": "419071"
    },
    {
      "ref": "claudiovalim/lgb-esemble-xgb-be-in-top-100-with-lb-0-285",
      "title": "Lgb Esemble + Xgb - Be in Top 100 with LB 0.285",
      "source": "live",
      "kernel_id": "418762"
    },
    {
      "ref": "claudiovalim/notebookd12bc12dd2",
      "title": "Notebookd12bc12dd2",
      "source": "live",
      "kernel_id": "418741"
    },
    {
      "ref": "suneelnair1/predictions-for-driver-claims",
      "title": "Predictions for driver claims",
      "source": "live",
      "kernel_id": "418034"
    },
    {
      "ref": "dataoleks/baseline-submission-balanced-logistic-regression",
      "title": "Baseline Submission. Balanced Logistic Regression",
      "source": "live",
      "kernel_id": "417554"
    },
    {
      "ref": "trakton/porto-seguro-dataanalysis-ensemble",
      "title": "Porto Seguro: DataAnalysis + Ensemble ",
      "source": "live",
      "kernel_id": "417053"
    },
    {
      "ref": "isaienkov/simple-autoencoder-for-ps-ind-06-bin-ps-ind-09-bin",
      "title": "Simple autoencoder for ps_ind_06_bin-ps_ind_09_bin",
      "source": "live",
      "kernel_id": "416756"
    },
    {
      "ref": "yekenot/2-level-stacker-silver-solution",
      "title": "2-level Stacker",
      "source": "live",
      "kernel_id": "415181"
    },
    {
      "ref": "oneonezero/handling-missing-values-a-clustering-approach",
      "title": "Handling missing values - a clustering approach",
      "source": "live",
      "kernel_id": "415027"
    },
    {
      "ref": "kueipo/base-on-froza-pascal-single-xgb-lb-0-284",
      "title": "Base on Froza & Pascal single XGB LB(0.284)",
      "source": "live",
      "kernel_id": "414689"
    },
    {
      "ref": "neviadomski/data-exploration-porto-seguro-s-safe-driver",
      "title": "Data Exploration Porto Seguro's Safe Driver",
      "source": "live",
      "kernel_id": "414250"
    },
    {
      "ref": "luanho/very-very-simple-approach-for-beginer",
      "title": "Very very simple approach for beginer",
      "source": "live",
      "kernel_id": "414164"
    },
    {
      "ref": "wangk4/notebook",
      "title": "Notebook",
      "source": "live",
      "kernel_id": "414087"
    },
    {
      "ref": "aharless/stacking-with-log-odds-and-no-intercept",
      "title": "Stacking with Log-Odds and No Intercept",
      "source": "live",
      "kernel_id": "413767"
    },
    {
      "ref": "bhavesh09/automl-h2o-trial",
      "title": "AutoML(h2o) Trial",
      "source": "live",
      "kernel_id": "413538"
    },
    {
      "ref": "zusmani/lgb-esemble-xgb-be-in-top-100-with-lb-0-285",
      "title": "Lgb Esemble + Xgb - Be in Top 100 with LB 0.285",
      "source": "live",
      "kernel_id": "413307"
    },
    {
      "ref": "abevieiramota/data-exploration",
      "title": "Data Exploration",
      "source": "live",
      "kernel_id": "413290"
    },
    {
      "ref": "bhavesh09/auto-ml-trial-in-r",
      "title": "Auto ML Trial in R",
      "source": "live",
      "kernel_id": "413181"
    },
    {
      "ref": "yakolle/porto-lgb-prune-ensemble",
      "title": "porto_lgb_prune_ensemble",
      "source": "live",
      "kernel_id": "412916"
    },
    {
      "ref": "tendolkar3/no-magic-0-283-lb-detailed-w-data-exploration",
      "title": "No Magic - 0.283 LB - Detailed w/ data exploration",
      "source": "live",
      "kernel_id": "412881"
    },
    {
      "ref": "ievgenvp/lgbm-custom-randomizedsearchcv-lb-283",
      "title": "LGBM custom RandomizedSearchCV (LB .283)",
      "source": "live",
      "kernel_id": "411443"
    },
    {
      "ref": "kosiew/rank-averaging-script",
      "title": "Rank Averaging script",
      "source": "live",
      "kernel_id": "411136"
    },
    {
      "ref": "mizioan/data-exploration-assisting-kernel-tensorflow",
      "title": "Data Exploration assisting kernel \"TensorFlow ..\"",
      "source": "live",
      "kernel_id": "410731"
    },
    {
      "ref": "loveall/stacking-lb-0-285-b2c342",
      "title": "Stacking - LB 0.285 b2c342",
      "source": "live",
      "kernel_id": "410539"
    },
    {
      "ref": "arthurlpgc/random-forest-try-3-on-porto-seguro",
      "title": "Random Forest Try #3 on Porto Seguro",
      "source": "live",
      "kernel_id": "410268"
    },
    {
      "ref": "keremt/predict-iterate-repeat-part1",
      "title": "PREDICT - ITERATE - REPEAT - PART1",
      "source": "live",
      "kernel_id": "409750"
    },
    {
      "ref": "priyasd/pca-on-seguro-s-data",
      "title": "PCA on Seguro's data",
      "source": "live",
      "kernel_id": "409508"
    },
    {
      "ref": "snowdog/old-school-nnet",
      "title": "Old school nnet",
      "source": "live",
      "kernel_id": "409408"
    },
    {
      "ref": "mizioan/tensorflow-with-2-layer-neural-network",
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      "ref": "felipeleiteantunes/xgboost-hyperopt-cv-via-python-api",
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      "ref": "bertcarremans/data-preparation-exploration",
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      "ref": "phamquoc94/3-lines-to-get-0-28-on-lb",
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      "ref": "felipeleiteantunes/h2o-ai-from-linear-models-to-deep-learning",
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      "ref": "danofer/xgb-onehot-encoding-lb-0-281",
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      "ref": "ashwinsr321/reducing-insurance-burden-on-safe-drivers",
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