A collection sklearn transformers to encode categorical variables as numeric
Project description
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A set of scikit-learn-style transformers for encoding categorical variables into numeric by means of different techniques.
Important Links
Documentation: [http://wdm0006.github.io/categorical_encoding/](http://wdm0006.github.io/categorical_encoding/)
Encoding Methods
Ordinal [2][3]
One-Hot [2][3]
Binary
Helmert Contrast [2][3]
Sum Contrast [2][3]
Polynomial Contrast [2][3]
Backward Difference Contrast [2][3]
Hashing [1]
Usage
The package by itself comes with a single module and an estimator. Before installing the module you will need numpy, statsmodels, and scipy.
To install the module execute:
`shell $ python setup.py install `
or
` pip install category_encoders `
or
` conda install -c conda-forge category_encoders `
To use:
import category_encoders as ce
encoder = ce.BackwardDifferenceEncoder(cols=[…]) encoder = ce.BinaryEncoder(cols=[…]) encoder = ce.HashingEncoder(cols=[…]) encoder = ce.HelmertEncoder(cols=[…]) encoder = ce.OneHotEncoder(cols=[…]) encoder = ce.OrdinalEncoder(cols=[…]) encoder = ce.SumEncoder(cols=[…]) encoder = ce.PolynomialEncoder(cols=[…])
All of these are fully compatible sklearn transformers, so they can be used in pipelines or in your existing scripts. If the cols parameter isn’t passed, every non-numeric column will be encoded. Please see the docs for transformer-specific configuration options.
Examples
In the examples directory, there is an example script used to benchmark different encoding techniques on various datasets.
The datasets used in the examples are car, mushroom, and splice datasets from the UCI dataset repository, found here:
[datasets](https://archive.ics.uci.edu/ml/datasets)
License
BSD 3-Clause
References:
Kilian Weinberger; Anirban Dasgupta; John Langford; Alex Smola; Josh Attenberg (2009). Feature Hashing for Large Scale Multitask Learning. Proc. ICML.
Contrast Coding Systems for categorical variables. UCLA: Statistical Consulting Group. from http://www.ats.ucla.edu/stat/r/library/contrast_coding.
Gregory Carey (2003). Coding Categorical Variables, from http://psych.colorado.edu/~carey/Courses/PSYC5741/handouts/Coding%20Categorical%20Variables%202006-03-03.pdf
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