![\"\"](\"http://www3.pictures.gi.zimbio.com/Fancy+Felines+Prep+Annual+Cat+Show+Madison+I-2X04SstdWl.jpg\")
Hello I already separated a material for this competition! Some works with categorical feature encoding !
\n\n
Going to be adding here more as I keep searching!
\n\n✔️ Permutation importance: a corrected feature importance measure
\n\nKernel example-Permutation importance: https://www.kaggle.com/caesarlupum/cat-with-null-importance-target-permutation/notebook
\n\n✔️ A frequency based encoding technique for transformation of categorical variables in mixed IVF dataset \n✔️ Similarity encoding for learning with dirty categorical variables\n✔️ Categorical encoding of color in the brain\n✔️ Encoding Categorical Variables with Conjugate Bayesian Models for WeWork Lead Scoring Engine\n✔️ An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing\n✔️Survey on Automated Machine Learning\n✔️ CatBoost: unbiased boosting with categorical features\n✔️ Encoding high-cardinality string categorical variables\n✔️A Comparative Study of Categorical Variable Encoding Techniques for Neural Network Classifiers
\n\n🐱 Techniques over Encrypted Data
\n\nLarge Scale Identity Deduplication Using Face Recognition Based on Facial Feature Points](https://www.sciencedirect.com/science/article/pii/S1877050916304628)
\n\nA Study on Deduplication Techniques over Encrypted Data
\n\n❤️ [Python Record Linkage Toolkit]\n(https://recordlinkage.readthedocs.io/en/latest/notebooks/data_deduplication.html)
\n\nRecordlinkage:A toolkit for record linkage and deduplication written in Python\n
\n\n🦉 Deduplication & Record Linkage
\n\nData deduplication: https://recordlinkage.readthedocs.io/en/latest/about.html#how-to-link-records
\n\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F3595464%2Fc24855d4aabb6e36f995e4a1ffe8f136%2Fdedupe.PNG?generation=1572456306985362&alt=media\")
🙌
\n\n💚 ✔️ Thanks Everyone✔️
", "messages": [ { "id": "711766", "postDate": "01/06/2020 14:32:42", "content": "Hello I already separated a material for this competition! Some works with categorical feature encoding !
\n\n
Going to be adding here more as I keep searching!
\n\n✔️ Permutation importance: a corrected feature importance measure
\n\nKernel example-Permutation importance: https://www.kaggle.com/caesarlupum/cat-with-null-importance-target-permutation/notebook
\n\n✔️ A frequency based encoding technique for transformation of categorical variables in mixed IVF dataset \n✔️ Similarity encoding for learning with dirty categorical variables\n✔️ Categorical encoding of color in the brain\n✔️ Encoding Categorical Variables with Conjugate Bayesian Models for WeWork Lead Scoring Engine\n✔️ An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing\n✔️Survey on Automated Machine Learning\n✔️ CatBoost: unbiased boosting with categorical features\n✔️ Encoding high-cardinality string categorical variables\n✔️A Comparative Study of Categorical Variable Encoding Techniques for Neural Network Classifiers
\n\n🐱 Techniques over Encrypted Data
\n\nLarge Scale Identity Deduplication Using Face Recognition Based on Facial Feature Points](https://www.sciencedirect.com/science/article/pii/S1877050916304628)
\n\nA Study on Deduplication Techniques over Encrypted Data
\n\n❤️ [Python Record Linkage Toolkit]\n(https://recordlinkage.readthedocs.io/en/latest/notebooks/data_deduplication.html)
\n\nRecordlinkage:A toolkit for record linkage and deduplication written in Python\n
\n\n🦉 Deduplication & Record Linkage
\n\nData deduplication: https://recordlinkage.readthedocs.io/en/latest/about.html#how-to-link-records
\n\n
🙌
\n\n💚 ✔️ Thanks Everyone✔️
", "rawMarkdown": "Hello I already separated a material for this [competition](https://www.kaggle.com/c/cat-in-the-dat-ii)! Some works with categorical feature encoding !\n\n\n\n\nGoing to be adding here more as I keep searching! \n\n✔️ [Permutation importance: a corrected feature importance measure](https://academic.oup.com/bioinformatics/article/26/10/1340/193348) \n\nKernel example-Permutation importance: https://www.kaggle.com/caesarlupum/cat-with-null-importance-target-permutation/notebook\n\n\n\n✔️ [A frequency based encoding technique for transformation of categorical variables in mixed IVF dataset](https://ieeexplore.ieee.org/abstract/document/5334548) \n✔️ [Similarity encoding for learning with dirty categorical variables](https://link.springer.com/article/10.1007/s10994-018-5724-2)\n✔️ [Categorical encoding of color in the brain](https://www.pnas.org/content/111/12/4590.short)\n✔️ [Encoding Categorical Variables with Conjugate Bayesian Models for WeWork Lead Scoring Engine](https://arxiv.org/abs/1904.13001)\n✔️ [An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing](http://www.diva-portal.se/smash/get/diva2:1259073/FULLTEXT01.pdf)\n✔️[Survey on Automated Machine Learning](https://arxiv.org/abs/1904.12054)\n✔️ [CatBoost: unbiased boosting with categorical features](http://papers.nips.cc/paper/7898-catboost-unbiased-boosting-with-categorical-features)\n✔️ [Encoding high-cardinality string categorical variables](http://https://arxiv.org/pdf/1907.01860.pdf)\n✔️[A Comparative Study of Categorical Variable Encoding Techniques for Neural Network Classifiers](http://https://www.researchgate.net/publication/320465713_A_Comparative_Study_of_Categorical_Variable_Encoding_Techniques_for_Neural_Network_Classifiers)\n\n\n\n\n🐱 Techniques over Encrypted Data\n\nLarge Scale Identity Deduplication Using Face Recognition Based on Facial Feature Points](https://www.sciencedirect.com/science/article/pii/S1877050916304628)\n\n[A Study on Deduplication Techniques over Encrypted Data](https://link.springer.com/chapter/10.1007/978-3-642-25449-9_4)\n\n❤️ [Python Record Linkage Toolkit]\n(https://recordlinkage.readthedocs.io/en/latest/notebooks/data_deduplication.html)\n\n[Recordlinkage:A toolkit for record linkage and deduplication written in Python\n](https://awesomeopensource.com/project/J535D165/recordlinkage)\n\n[🦉 Deduplication & Record Linkage](https://www.kaggle.com/caesarlupum/deduplication-record-linkage?scriptVersionId=23043349)\n\n\n\nData deduplication: https://recordlinkage.readthedocs.io/en/latest/about.html#how-to-link-records\n\n\n\n\n🙌 \n\n💚 ✔️ Thanks Everyone✔️", "votes": null }, { "id": "711829", "postDate": "01/06/2020 15:04:43", "content": "Thanks! Upvoted!
", "rawMarkdown": "Thanks! Upvoted!", "votes": null }, { "id": "711852", "postDate": "01/06/2020 15:24:55", "content": "Thanks @franciscoescobar !
\n\nAnother interesting topic, by @brunhs : https://www.kaggle.com/c/cat-in-the-dat/discussion/105512
", "rawMarkdown": "Thanks @franciscoescobar !\n\nAnother interesting topic, by @brunhs : https://www.kaggle.com/c/cat-in-the-dat/discussion/105512", "votes": null }, { "id": "712042", "postDate": "01/06/2020 19:12:21", "content": "Excellent Material.
", "rawMarkdown": "Excellent Material.", "votes": null }, { "id": "712058", "postDate": "01/06/2020 19:22:48", "content": "Thanks @mpwolke ! In my opinion, is very important for real life
", "rawMarkdown": "Thanks @mpwolke ! In my opinion, is very important for real life", "votes": null }, { "id": "712640", "postDate": "01/07/2020 13:20:38", "content": "This is great and something different. Well done !
", "rawMarkdown": "This is great and something different. Well done !", "votes": null }, { "id": "712683", "postDate": "01/07/2020 13:55:16", "content": "Thanks @atulanandjha!
", "rawMarkdown": "Thanks @atulanandjha!", "votes": null }, { "id": "712684", "postDate": "01/07/2020 13:56:18", "content": "Happy New Year buddy !
", "rawMarkdown": "Happy New Year buddy !", "votes": null }, { "id": "712921", "postDate": "01/07/2020 18:21:37", "content": "Happy new year. Thanks for connecting also.
", "rawMarkdown": "Happy new year. Thanks for connecting also.", "votes": null }, { "id": "714312", "postDate": "01/09/2020 09:36:12", "content": "Great, bookmarked! 💯
", "rawMarkdown": "Great, bookmarked! 💯", "votes": null }, { "id": "714488", "postDate": "01/09/2020 13:44:00", "content": "Thanks bro !
", "rawMarkdown": "Thanks bro !", "votes": null }, { "id": "714490", "postDate": "01/09/2020 13:47:42", "content": "@dasmehdixtr maybe you can see the dataset, Vertebral Column: https://www.kaggle.com/caesarlupum/vertebralcolumndataset
\n\nDataSet containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).
", "rawMarkdown": "@dasmehdixtr maybe you can see the dataset, Vertebral Column: https://www.kaggle.com/caesarlupum/vertebralcolumndataset\n\nDataSet containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).", "votes": null }, { "id": "714691", "postDate": "01/09/2020 16:43:49", "content": "Yes, I'm interesting in biomechanics.Nice dataset.You can check my profile too.I will use that dataset.
", "rawMarkdown": "Yes, I'm interesting in biomechanics.Nice dataset.You can check my profile too.I will use that dataset.", "votes": null }, { "id": "714719", "postDate": "01/09/2020 17:24:55", "content": "Of course @dasmehdixtr !Thanks !
", "rawMarkdown": "Of course @dasmehdixtr !Thanks !", "votes": null } ], "comments": [ { "id": 711829, "author_name": "franciscoescobar", "author_url": "", "post_date": "01/06/2020 15:04:43", "content": "Thanks! Upvoted!
", "votes": null, "replies": [ { "id": 711852, "author_name": "caesarlupum", "author_url": "", "post_date": "01/06/2020 15:24:55", "content": "Thanks @franciscoescobar !
\n\nAnother interesting topic, by @brunhs : https://www.kaggle.com/c/cat-in-the-dat/discussion/105512
", "votes": null, "replies": [] } ] }, { "id": 712042, "author_name": "mpwolke", "author_url": "", "post_date": "01/06/2020 19:12:21", "content": "Excellent Material.
", "votes": null, "replies": [ { "id": 712058, "author_name": "caesarlupum", "author_url": "", "post_date": "01/06/2020 19:22:48", "content": "Thanks @mpwolke ! In my opinion, is very important for real life
", "votes": null, "replies": [] } ] }, { "id": 712640, "author_name": "atulanandjha", "author_url": "", "post_date": "01/07/2020 13:20:38", "content": "This is great and something different. Well done !
", "votes": null, "replies": [ { "id": 712683, "author_name": "caesarlupum", "author_url": "", "post_date": "01/07/2020 13:55:16", "content": "Thanks @atulanandjha!
", "votes": null, "replies": [] }, { "id": 712684, "author_name": "caesarlupum", "author_url": "", "post_date": "01/07/2020 13:56:18", "content": "Happy New Year buddy !
", "votes": null, "replies": [] }, { "id": 712921, "author_name": "atulanandjha", "author_url": "", "post_date": "01/07/2020 18:21:37", "content": "Happy new year. Thanks for connecting also.
", "votes": null, "replies": [] } ] }, { "id": 714312, "author_name": "dasmehdixtr", "author_url": "", "post_date": "01/09/2020 09:36:12", "content": "Great, bookmarked! 💯
", "votes": null, "replies": [ { "id": 714488, "author_name": "caesarlupum", "author_url": "", "post_date": "01/09/2020 13:44:00", "content": "Thanks bro !
", "votes": null, "replies": [] }, { "id": 714490, "author_name": "caesarlupum", "author_url": "", "post_date": "01/09/2020 13:47:42", "content": "@dasmehdixtr maybe you can see the dataset, Vertebral Column: https://www.kaggle.com/caesarlupum/vertebralcolumndataset
\n\nDataSet containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).
", "votes": null, "replies": [] }, { "id": 714691, "author_name": "dasmehdixtr", "author_url": "", "post_date": "01/09/2020 16:43:49", "content": "Yes, I'm interesting in biomechanics.Nice dataset.You can check my profile too.I will use that dataset.
", "votes": null, "replies": [] }, { "id": 714719, "author_name": "caesarlupum", "author_url": "", "post_date": "01/09/2020 17:24:55", "content": "Of course @dasmehdixtr !Thanks !
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "711766": "Hello I already separated a material for this [competition](https://www.kaggle.com/c/cat-in-the-dat-ii)! Some works with categorical feature encoding !\n\n\n\n\nGoing to be adding here more as I keep searching! \n\n✔️ [Permutation importance: a corrected feature importance measure](https://academic.oup.com/bioinformatics/article/26/10/1340/193348) \n\nKernel example-Permutation importance: https://www.kaggle.com/caesarlupum/cat-with-null-importance-target-permutation/notebook\n\n\n\n✔️ [A frequency based encoding technique for transformation of categorical variables in mixed IVF dataset](https://ieeexplore.ieee.org/abstract/document/5334548) \n✔️ [Similarity encoding for learning with dirty categorical variables](https://link.springer.com/article/10.1007/s10994-018-5724-2)\n✔️ [Categorical encoding of color in the brain](https://www.pnas.org/content/111/12/4590.short)\n✔️ [Encoding Categorical Variables with Conjugate Bayesian Models for WeWork Lead Scoring Engine](https://arxiv.org/abs/1904.13001)\n✔️ [An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing](http://www.diva-portal.se/smash/get/diva2:1259073/FULLTEXT01.pdf)\n✔️[Survey on Automated Machine Learning](https://arxiv.org/abs/1904.12054)\n✔️ [CatBoost: unbiased boosting with categorical features](http://papers.nips.cc/paper/7898-catboost-unbiased-boosting-with-categorical-features)\n✔️ [Encoding high-cardinality string categorical variables](http://https://arxiv.org/pdf/1907.01860.pdf)\n✔️[A Comparative Study of Categorical Variable Encoding Techniques for Neural Network Classifiers](http://https://www.researchgate.net/publication/320465713_A_Comparative_Study_of_Categorical_Variable_Encoding_Techniques_for_Neural_Network_Classifiers)\n\n\n\n\n🐱 Techniques over Encrypted Data\n\nLarge Scale Identity Deduplication Using Face Recognition Based on Facial Feature Points](https://www.sciencedirect.com/science/article/pii/S1877050916304628)\n\n[A Study on Deduplication Techniques over Encrypted Data](https://link.springer.com/chapter/10.1007/978-3-642-25449-9_4)\n\n❤️ [Python Record Linkage Toolkit]\n(https://recordlinkage.readthedocs.io/en/latest/notebooks/data_deduplication.html)\n\n[Recordlinkage:A toolkit for record linkage and deduplication written in Python\n](https://awesomeopensource.com/project/J535D165/recordlinkage)\n\n[🦉 Deduplication & Record Linkage](https://www.kaggle.com/caesarlupum/deduplication-record-linkage?scriptVersionId=23043349)\n\n\n\nData deduplication: https://recordlinkage.readthedocs.io/en/latest/about.html#how-to-link-records\n\n\n\n\n🙌 \n\n💚 ✔️ Thanks Everyone✔️", "711829": "Thanks! Upvoted!", "711852": "Thanks @franciscoescobar !\n\nAnother interesting topic, by @brunhs : https://www.kaggle.com/c/cat-in-the-dat/discussion/105512", "712042": "Excellent Material.", "712058": "Thanks @mpwolke ! In my opinion, is very important for real life", "712640": "This is great and something different. Well done !", "712683": "Thanks @atulanandjha!", "712684": "Happy New Year buddy !", "712921": "Happy new year. Thanks for connecting also.", "714312": "Great, bookmarked! 💯", "714488": "Thanks bro !", "714490": "@dasmehdixtr maybe you can see the dataset, Vertebral Column: https://www.kaggle.com/caesarlupum/vertebralcolumndataset\n\nDataSet containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).", "714691": "Yes, I'm interesting in biomechanics.Nice dataset.You can check my profile too.I will use that dataset.", "714719": "Of course @dasmehdixtr !Thanks !" }, "source": "meta" }