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我正在嘗試爲文本分類管道生成PMML（使用jpmml-sklearn）。代碼中的最後一行 - sklearn2pmml（Textpipeline，「TextMiningClassifier.pmml」，with_repr = True） - 崩潰。在python中生成用於文本分類管道的PMML
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.linear_model import SGDClassifier
from sklearn2pmml import PMMLPipeline
categories = [
'alt.atheism',
'talk.religion.misc',
]
print("Loading 20 newsgroups dataset for categories:")
print(categories)
data = fetch_20newsgroups(subset='train', categories=categories)
print("%d documents" % len(data.filenames))
print("%d categories" % len(data.target_names))
Textpipeline = PMMLPipeline([
('vect', CountVectorizer()),
('tfidf', TfidfTransformer()),
('clf', SGDClassifier()),
])
Textpipeline.fit(data.data, data.target)
from sklearn2pmml import sklearn2pmml
sklearn2pmml(Textpipeline, "TextMiningClassifier.pmml", with_repr = True)
看起來像sklearn2pmml（）不能將Textpipeline作爲輸入。該代碼適用於其他管道（示例在這裏：https://github.com/jpmml/sklearn2pmml），但不適用於上面的文本分類管道。所以我的問題是：如何爲文本分類問題生成PMML？
錯誤，我得到：
Jun 15, 2017 12:48:00 PM org.jpmml.sklearn.Main run
INFO: Parsing PKL..
Jun 15, 2017 12:48:01 PM org.jpmml.sklearn.Main run
INFO: Parsed PKL in 489 ms.
Jun 15, 2017 12:48:01 PM org.jpmml.sklearn.Main run
INFO: Converting..
Jun 15, 2017 12:48:01 PM sklearn2pmml.PMMLPipeline encodePMML
WARNING: The 'target_field' attribute is not set. Assuming y as the name of the target field
Jun 15, 2017 12:48:01 PM sklearn2pmml.PMMLPipeline initFeatures
WARNING: The 'active_fields' attribute is not set. Assuming [x1] as the names of active fields
Jun 15, 2017 12:48:01 PM org.jpmml.sklearn.Main run
SEVERE: Failed to convert
java.lang.IllegalArgumentException: The tokenizer object (null) is not Splitter
at sklearn.feature_extraction.text.CountVectorizer.getTokenizer(CountVectorizer.java:263)
at sklearn.feature_extraction.text.CountVectorizer.encodeDefineFunction(CountVectorizer.java:164)
at sklearn.feature_extraction.text.CountVectorizer.encodeFeatures(CountVectorizer.java:124)
at sklearn.pipeline.Pipeline.encodeFeatures(Pipeline.java:93)
at sklearn2pmml.PMMLPipeline.encodePMML(PMMLPipeline.java:122)
at org.jpmml.sklearn.Main.run(Main.java:144)
at org.jpmml.sklearn.Main.main(Main.java:93)
Exception in thread "main" java.lang.IllegalArgumentException: The tokenizer object (null) is not Splitter
at sklearn.feature_extraction.text.CountVectorizer.getTokenizer(CountVectorizer.java:263)
at sklearn.feature_extraction.text.CountVectorizer.encodeDefineFunction(CountVectorizer.java:164)
at sklearn.feature_extraction.text.CountVectorizer.encodeFeatures(CountVectorizer.java:124)
at sklearn.pipeline.Pipeline.encodeFeatures(Pipeline.java:93)
at sklearn2pmml.PMMLPipeline.encodePMML(PMMLPipeline.java:122)
at org.jpmml.sklearn.Main.run(Main.java:144)
at org.jpmml.sklearn.Main.main(Main.java:93)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Data\Anaconda2\lib\site-packages\sklearn2pmml\__init__.py", line 142, in sklearn2pmml
raise RuntimeError("The JPMML-SkLearn conversion application has failed. The Java process should have printed more information about the failure into its standard output and/or error streams")
RuntimeError: The JPMML-SkLearn conversion application has failed. The Java process should have printed more information about the failure into its standard output and/or error streams