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JPMML-StatsModels

Java library and command-line application for converting StatsModels models to PMML.

Features

• Supported model types:
  • Linear Regression:
    • Ordinary Least Squares
    • Quantile Regression
    • Weighted Least Squares
  • Generalized Linear Regression:
    • Generalized Linear Models:
      • Families: Binomial, Gaussian, Poisson
      • Link Functions: identity, Log, Logit
  • Regression with Discrete Dependent Variable:
    • Logit
    • Multinomial Logit
    • Poisson
    • OrderedModel:
      • Distributions: logit, probit
• Production quality:
  • Complete test coverage.
  • Fully compliant with the JPMML-Evaluator library.

Installation

Enter the project root directory and build using Apache Maven:

mvn clean install

The build produces a library JAR file pmml-statsmodels/target/pmml-statsmodels-1.1-SNAPSHOT.jar, and an executable uber-JAR file pmml-statsmodels-example/target/pmml-statsmodels-example-executable-1.1-SNAPSHOT.jar.

Usage

A typical workflow can be summarized as follows:

1. Use Python to fit a model.
2. Save the model fitting results in pickle data format to a file in a local filesystem.
3. Use the JPMML-StatsModels command-line converter application to turn the Pickle file to a PMML file.

The Python side of operations

Loading data to a pandas.DataFrame object:

import pandas

auto_df = pandas.read_csv("Auto.csv")

Fitting a regression model using an R-style formula:

from statsmodels.formula.api import ols

model = ols(formula = "mpg ~ C(cylinders) + displacement + horsepower + weight + acceleration + C(model_year) + C(origin)", data = auto_df)
results = model.fit()
print(results.summary())

Storing the fitted RegressionResults(Wrapper) object in pickle data format:

results.save("model.pkl", remove_data = True)

The JPMML-StatsModels side of operations

Converting the model fitting results Pickle file model.pkl to a PMML file model.pmml:

java -jar pmml-statsmodels-example/target/pmml-statsmodels-example-executable-1.1-SNAPSHOT.jar --pkl-input model.pkl --pmml-output model.pmml

Getting help:

java -jar pmml-statsmodels-example/target/pmml-statsmodels-example-executable-1.1-SNAPSHOT.jar --help

Documentation

• Training Scikit-Learn GridSearchCV StatsModels pipelines
• Training Scikit-Learn StatsModels pipelines

License

JPMML-StatsModels is licensed under the terms and conditions of the GNU Affero General Public License, Version 3.0.

If you would like to use JPMML-StatsModels in a proprietary software project, then it is possible to enter into a licensing agreement which makes JPMML-StatsModels available under the terms and conditions of the BSD 3-Clause License instead.

Additional information

JPMML-StatsModels is developed and maintained by Openscoring Ltd, Estonia.

Interested in using Java PMML API software in your company? Please contact info@openscoring.io