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Binary classification, with every feature as categoricals

Home Page: https://www.kaggle.com/praxitelisk/categorical-feature-encoding-challenge-eda-ml

License: MIT License

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machine-learning exploratory-data-analysis class-imbalance categorical-features kaggle-competition python3 jupyter-notebook xgboost random-forest

categorical-feature-encoding-challenge's Introduction

Categorical-Feature-Encoding-Challenge

A common task in machine learning pipelines is encoding categorical variables for a given algorithm in a format that allows as much useful signal as possible to be captured.

Because this is such a common task and important skill to master, we've put together a dataset that contains only categorical features, and includes:

binary features low- and high-cardinality nominal features low- and high-cardinality ordinal features (potentially) cyclical features This Playground competition will give you the opportunity to try different encoding schemes for different algorithms to compare how they perform. We encourage you to share what you find with the community.

Competition link.

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