- December 29, 2017
- Cyanny Liang
On the last day before the New Year Holiday, ppmml is published.
ppmml is a python library for converting machine learning models to pmml file. ppmml wraps jpmml libraries and provides clean interface.
PMML - “Predictive Model Markup Language”, which is a standard for XML documents which express trained instances of analytic models.
Various platforms adopt pmml as machine learning model standard, including IBM, SAS, Microsoft, Spark, KNIME etd.pmml-platforms
jpmml has developed pmml model library and supported models of spark, xgboost, tensorflow, sklearn, lightgbm and R. All of these libraries are separated and written in java.
ppmml wraps jpmml libraries and proved a simple and easy-to-use API for pmml files transformation.
0.0.1 version supports sklearn, tensorflow, spark, lightgbm, xgboost and R models. All models supported by jpmml are supported by ppmml. Common machine learning algorithms are supported, such as Decision Tree, Logistic Regression, GBDT, Random Forest, KMeans. However, Deep Learning support is not ready.