sklearn2pmml save machine learning model error

Question

I was recently looking for a solution to transfer machine learning model across platforms between python and java. In other words, firstly train machine learning model with python, then carry out prediction on line with java. Fortunately, I found out sklearn2pmml. however, I hit the java error when trying to use the basic usage examples，the error resulted in the saved empty file. code as follows:

from sklearn_pandas import DataFrameMapper    
import pandas as pd
import numpy as np
from sklearn2pmml import sklearn2pmml,PMMLPipeline
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import MinMaxScaler,LabelBinarizer,FunctionTransformer
heart_data = pd.read_csv("heart.csv")
# 用Mapper定义特征工程
mapper = DataFrameMapper([
    (['sbp'], MinMaxScaler()),
    (['tobacco'], MinMaxScaler()),
    ('ldl', None),
    ('adiposity', None),
    (['famhist'], LabelBinarizer()),
    ('typea', None),
    ('obesity', None),
    ('alcohol', None),
    (['age'], FunctionTransformer(np.log)),
]) 
#用pipeline定义使用的模型，特征工程等
pipeline = PMMLPipeline([
   ('mapper', mapper),
   ("classifier", LinearRegression())
])

pipeline.fit(heart_data[heart_data.columns.difference(["chd"])], heart_data["chd"])   # 排除某些列，使用df.columns.difference(['列名'])
#导出模型文件
sklearn2pmml(pipeline, "lrHeart.xml", with_repr = True)

error as follows:

Standard output is empty
Standard error:
2月 24, 2018 3:55:48 下午 org.jpmml.sklearn.Main run
信息: Parsing PKL..
2月 24, 2018 3:55:48 下午 org.jpmml.sklearn.Main run
信息: Parsed PKL in 42 ms.
2月 24, 2018 3:55:48 下午 org.jpmml.sklearn.Main run
信息: Converting..
2月 24, 2018 3:55:48 下午 org.jpmml.sklearn.Main run
信息: Converted in 119 ms.
2月 24, 2018 3:55:48 下午 org.jpmml.sklearn.Main run
信息: Marshalling PMML..
Exception in thread "main" java.lang.NoClassDefFoundError: javax/xml/bind/JAXBContext
    at org.jpmml.model.JAXBUtil.getContext(JAXBUtil.java:126)
    at org.jpmml.model.MetroJAXBUtil.marshalPMML(MetroJAXBUtil.java:25)
    at org.jpmml.sklearn.Main.run(Main.java:159)
    at org.jpmml.sklearn.Main.main(Main.java:94)
Caused by: java.lang.ClassNotFoundException: javax.xml.bind.JAXBContext
    at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:582)
    at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:185)
    at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:496)
    ... 4 more

---------------------------------------------------------------------------
RuntimeError                          

        Traceback (most recent call last)
    <ipython-input-2-8e79360b3ddd> in <module>()


    20 pipeline.fit(heart_data[heart_data.columns.difference(["chd"])], heart_data["chd"])   # 排除某些列，使用df.columns.difference(['列名'])
         21 #导出模型文件
    ---> 22sklearn2pmml(pipeline, "lrHeart.xml", with_repr = True)

~/anaconda3/lib/python3.6/site-packages/sklearn2pmml/__init__.py in sklearn2pmml(pipeline, pmml, user_classpath, with_repr, debug)
    304                                 print("Standard error is empty")
    305                 if retcode:
--> 306                         raise RuntimeError("The JPMML-SkLearn conversion application has failed. The Java executable should have printed more information about the failure into its standard output and/or standard error streams")
    307         finally:
    308                 if debug:

RuntimeError: The JPMML-SkLearn conversion application has failed. The Java executable should have printed more information about the failure into its standard output and/or standard error streams

Answer 1

Are you using Java(.exe) version 9? If so, then you should (at least temporarily) downgrade to Java version 8, because the sklearn2pmml package is not properly configured for newer versions yet. See https://github.com/jpmml/sklearn2pmml/issues/80