在Python 3.6中调用sklearn2pmml（）函数会抛出RuntimeError

Question

我正在尝试将Pipeline对象保存为PMML，而Python会抛出RuntimeError。

我的Python版本是3.6，sklearn2pmml版本是0.44.0，JDK版本是1.8.0_201。

所有这些都符合包的先决条件。

这是我到目前为止所做的。 （我不包括数据加载和清理部分）

from sklearn2pmml.pipeline import PMMLPipeline
from sklearn2pmml import make_pmml_pipeline, sklearn2pmml

logit_pipline = Pipeline([('vect', CountVectorizer(ngram_range=(1,2))), ('tfidf', TfidfTransformer(use_idf=True)), ('clf', LogisticRegression(C=11.3))])
pmml_pipeline = PMMLPipeline([("logit", logit_pipline)])
pmml_pipeline.fit(X, Y)

sklearn2pmml(pmml_pipeline, 'logit.pmml', with_repr=True)

在我运行上面提到的最后一行之后发生了什么......

sklearn2pmml(pmml_pipeline, 'logit.pmml', with_repr=True)
Standard output is empty
Standard error:
Apr 30, 2019 11:59:04 AM org.jpmml.sklearn.Main run
INFO: Parsing PKL..
Apr 30, 2019 11:59:04 AM org.jpmml.sklearn.Main run
INFO: Parsed PKL in 230 ms.
Apr 30, 2019 11:59:04 AM org.jpmml.sklearn.Main run
INFO: Converting..
Apr 30, 2019 11:59:04 AM org.jpmml.sklearn.Main run
SEVERE: Failed to convert
java.lang.IllegalArgumentException: Expected an estimator object as the last step, got a transformer object (Python class sklearn.pipeline.Pipeline)
        at sklearn2pmml.pipeline.PMMLPipeline.getEstimator(PMMLPipeline.java:541)
        at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:93)
        at org.jpmml.sklearn.Main.run(Main.java:145)
        at org.jpmml.sklearn.Main.main(Main.java:94)

Exception in thread "main" java.lang.IllegalArgumentException: Expected an estimator object as the last step, got a transformer object (Python class sklearn.pipeline.Pipeline)
        at sklearn2pmml.pipeline.PMMLPipeline.getEstimator(PMMLPipeline.java:541)
        at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:93)
        at org.jpmml.sklearn.Main.run(Main.java:145)
        at org.jpmml.sklearn.Main.main(Main.java:94)

Traceback (most recent call last):

  File "<ipython-input-129-f5c307b4aaba>", line 1, in <module>
    sklearn2pmml(pmml_pipeline, 'logit.pmml', with_repr=True)

  File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn2pmml\__init__.py", line 252, in sklearn2pmml
    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")

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

现在根据一些人的说法，这是一些JDK兼容性问题，使用JDK 1.9及以上版本或1.6及以下版本会引发这类问题。但由于我的JDK版本可以被sklearn2pmml接受，为什么会出现这种错误呢？

Answer 1

正如底层Java异常所述，sklearn2pmml.pipeline.PMMLPipeline类需要使用一系列步骤进行参数化，其中最后一步包含一些估算器对象。在您的情况下，您正在使用单个元素的步骤列表来参数化PMMLPipeline;最后一步包含一个Pipeline对象，在这个意义上它不是一个估计对象。

要解决这个问题，只需摆脱中间的logit_pipline层（无论如何，在管道内包装管道的想法是什么？）。

例如，这可以工作：

logit_pipline = PMMLPipeline([..])
logit_pipeline.fit(X, y)
sklearn2pmml(logit_pipeline, "logit.pmml")

此问题与JDK，Python或Scikit-Learn版本完全无关。