sklearn2pmml错误：用于构造ClassDict的预期零参数（对于pandas._libs.interval.Interval）

Question

在训练LR模型时，我使用sklearn2pmml.preprocessing.CutTransformer和sklearn.preprocessing.LabelEncoder编码了目标。

这是我的代码：

from sklearn2pmml.preprocessing import CutTransformer
from sklearn.preprocessing.label import LabelEncoder
income_bins = [-np.inf, 10000, 50000, 100000, 300000, 500000, 1000000, 3000000, 5000000, 10000000, np.inf]

targetDiscretizer = PMMLPipeline([('target', 
                               DataFrameMapper([
                                   (['income'], [CutTransformer(bins=income_bins), LabelEncoder()])
                               ])
                              )])
dataset['target_income_lvl'] = targetDiscretizer.fit_transform(dataset)
sklearn2pmml(targetDiscretizer, '../model/targetDiscretizer.pmml', with_repr=True )

但是我得到一个错误：

net.razorvine.pickle.PickleException: expected zero arguments for construction of ClassDict (for pandas._libs.interval.Interval)
    at net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
    at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:732)
    at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:200)
    at net.razorvine.pickle.Unpickler.load(Unpickler.java:122)
    at numpy.core.NDArrayUtil.readObject(NDArrayUtil.java:384)
    at numpy.core.NDArrayUtil.access$700(NDArrayUtil.java:42)
    at numpy.core.NDArrayUtil$TypeDescriptor.read(NDArrayUtil.java:542)
    at numpy.core.NDArrayUtil.parseArray(NDArrayUtil.java:215)
    at numpy.core.NDArrayUtil.parseData(NDArrayUtil.java:190)
    at joblib.NumpyArrayWrapper.toArray(NumpyArrayWrapper.java:43)
    at org.jpmml.sklearn.PickleUtil$1.dispatch(PickleUtil.java:88)
    at net.razorvine.pickle.Unpickler.load(Unpickler.java:122)
    at org.jpmml.sklearn.PickleUtil.unpickle(PickleUtil.java:98)
    at org.jpmml.sklearn.Main.run(Main.java:104)
    at org.jpmml.sklearn.Main.main(Main.java:94)

Exception in thread "main" net.razorvine.pickle.PickleException: expected zero arguments for construction of ClassDict (for pandas._libs.interval.Interval)
at net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:732)
at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:200)
at net.razorvine.pickle.Unpickler.load(Unpickler.java:122)
at numpy.core.NDArrayUtil.readObject(NDArrayUtil.java:384)
at numpy.core.NDArrayUtil.access$700(NDArrayUtil.java:42)
at numpy.core.NDArrayUtil$TypeDescriptor.read(NDArrayUtil.java:542)
at numpy.core.NDArrayUtil.parseArray(NDArrayUtil.java:215)
at numpy.core.NDArrayUtil.parseData(NDArrayUtil.java:190)
at joblib.NumpyArrayWrapper.toArray(NumpyArrayWrapper.java:43)
at org.jpmml.sklearn.PickleUtil$1.dispatch(PickleUtil.java:88)
at net.razorvine.pickle.Unpickler.load(Unpickler.java:122)
at org.jpmml.sklearn.PickleUtil.unpickle(PickleUtil.java:98)
at org.jpmml.sklearn.Main.run(Main.java:104)
at org.jpmml.sklearn.Main.main(Main.java:94)

我对此一无所知。 有谁能够帮助我？

Answer 1

默认情况下，用于Python泡菜文件的Java解析器不了解非标准CPython类，例如pandas._libs.interval.Interval 。 每个CPython类都需要分别教它。 例如，SkLearn2PMML问题跟踪器中有一个相关的错误报告： https : //github.com/jpmml/sklearn2pmml/issues/115

如果您（至少是暂时地）设法抑制了pandas._libs.interval.Interval对象的生成，则该转换将起作用。 最可能的来源是自动生成的bin标签。 因此，尝试使用labels参数明确提供bin标签： CutTransformer(bins = income_bins, labels = income_bin_labels) 。