A library that allows serialization of SciKit-Learn estimators into PMML
Project description
[](https://travis-ci.org/alex-pirozhenko/sklearn-pmml) [](https://gitter.im/alex-pirozhenko/sklearn-pmml?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
# sklearn-pmml
A library that allows serialization of SciKit-Learn estimators into PMML
# Installation The easiest way is to use pip: ` pip install sklearn-pmml `
# Supported models - DecisionTreeClassifier - DecisionTreeRegressor - GradientBoostingClassifier - RandomForestClassifier
# PMML output
## Classification Classifier converters can only operate with categorical outputs, and for each categorical output variable `varname` the PMML output contains the following outputs: - categorical `varname` for the predicted label of the instance - double `varname.label` for the probability for a given label
## Regression Regression model PMML outputs the numeric response variable named as the output variable
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