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scorecard,model

Project description

LAPRAS

PyPi version Python version

Lapras is designed to make the model developing work easily and conveniently. It contains these functions below in one key operation: data exploratory analysis, feature selection, feature binning, data visualization, scorecard modeling(a logistic regression model with excellent interpretability), performance measure.

Let's get started.

Usage

1.Exploratory Data Analysis
lapras.detect()
lapras.quality()
lapras.IV()
lapras.VIF()
lapras.PSI()

2.Feature Selection
lapras.select()
lapras.stepwise()

3.Binning
lapras.Combiner()
lapras.WOETransformer()
lapras.bin_stats()
lapras.bin_plot()

4.Modeling
lapras.ScoreCard()

5.Performance Measure
lapras.perform()
lapras.LIFT()
lapras.score_plot()
lapras.KS_bucket()
lapras.PPSI()
lapras.KS()
lapras.AUC()

6.One Key Auto Modeling
Lapras also provides a function which runs all the steps above automatically:
lapras.auto_model()

For more details, please refer to the wiki page. Enjoy.

Install

via pip

pip install lapras --upgrade -i https://pypi.org/simple

via source code

python setup.py install

install_requires = [ 'numpy >= 1.18.4', 'pandas >= 0.25.1, <=0.25.3', 'scipy >= 1.3.2', 'scikit-learn =0.22.2', 'seaborn >= 0.10.1', 'statsmodels >= 0.13.1', 'tensorflow >= 2.2.0, <=2.5.0', 'hyperopt >= 0.2.7', 'pickle >= 4.0', ]

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