sklearn2pmml和jpmml sklearn使用错误

Question

我最近在寻找将scikit学习模型转换为PMML的方法时遇到了sklearn2pmml和jpmml sklearn。然而，我在尝试使用我无法理解的基本用法示例时遇到了错误。

当尝试在sklearn2pmml中使用示例时，我收到了以下关于将long转换为int的问题：

Exception in thread "main" java.lang.ClassCastException: java.lang.Long cannot be cast to java.lang.Integer
    at numpy.core.NDArrayUtil.getShape(NDArrayUtil.java:66)
    at org.jpmml.sklearn.ClassDictUtil.getShape(ClassDictUtil.java:92)
    at org.jpmml.sklearn.ClassDictUtil.getShape(ClassDictUtil.java:76)
    at sklearn.linear_model.BaseLinearClassifier.getCoefShape(BaseLinearClassifier.java:144)
    at sklearn.linear_model.BaseLinearClassifier.getNumberOfFeatures(BaseLinearClassifier.java:56)
    at sklearn.Classifier.createSchema(Classifier.java:50)
    at org.jpmml.sklearn.Main.run(Main.java:104)
    at org.jpmml.sklearn.Main.main(Main.java:87)
Traceback (most recent call last):
  File "C:Usersuserworkspacesklearn_pmmltest.py", line 40, in <module>
    sklearn2pmml(iris_classifier, iris_mapper, "LogisticRegressionIris.pmml")
  File "C:Python27libsite-packagessklearn2pmml__init__.py", line 49, in sklearn2pmml
    os.remove(dump)
WindowsError: [Error 32] The process cannot access the file because it is being used by another process: 'c:\users\user\appdata\local\temp\tmpmxyp2y.pkl'

关于这里发生的事情有什么建议吗？

使用代码：

#
# Step 1: feature engineering
#
from sklearn.datasets import load_iris
from sklearn.decomposition import PCA
import pandas
import sklearn_pandas
iris = load_iris()
iris_df = pandas.concat((pandas.DataFrame(iris.data[:, :], columns = ["Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width"]), pandas.DataFrame(iris.target, columns = ["Species"])), axis = 1)
iris_mapper = sklearn_pandas.DataFrameMapper([
    (["Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width"], PCA(n_components = 3)),
    ("Species", None)
])
iris = iris_mapper.fit_transform(iris_df)
#
# Step 2: training a logistic regression model
#
from sklearn.linear_model import LogisticRegressionCV
iris_X = iris[:, 0:3]
iris_y = iris[:, 3]
iris_classifier = LogisticRegressionCV()
iris_classifier.fit(iris_X, iris_y)
#
# Step 3: conversion to PMML
#
from sklearn2pmml import sklearn2pmml
sklearn2pmml(iris_classifier, iris_mapper, "LogisticRegressionIris.pmml")

编辑12/6:在新的更新之后，同样的问题进一步出现：

Dec 06, 2015 5:56:49 PM sklearn_pandas.DataFrameMapper updatePMML
INFO: Updating 1 target field and 3 active field(s)
Dec 06, 2015 5:56:49 PM sklearn_pandas.DataFrameMapper updatePMML
INFO: Mapping target field y to Species
Dec 06, 2015 5:56:49 PM sklearn_pandas.DataFrameMapper updatePMML
INFO: Mapping active field(s) [x1, x2, x3] to [Sepal.Length, Sepal.Width, Petal.Length, Petal.Width]
Traceback (most recent call last):
  File "C:Usersuserworkspacesklearn_pmmltest.py", line 40, in <module>
    sklearn2pmml(iris_classifier, iris_mapper, "LogisticRegressionIris.pmml")
  File "C:Python27libsite-packagessklearn2pmml__init__.py", line 49, in sklearn2pmml
    os.remove(dump)
WindowsError: [Error 32] The process cannot access the file because it is being used by another process: 'c:\users\user\appdata\local\temp\tmpqeblat.pkl'

Answer 1

JPMML SkLearn预期ndarray.shape是i4的元组（由热解岩库映射到java.lang.Integer）。然而，在这种情况下，它是i8的元组（映射到java.lang.Long）。因此出现了强制转换异常。

这个问题已经在JPMML SkLearn提交f7c16ac2fb中得到了解决。

如果你遇到了另一个异常（平台之间的数据转换可能很棘手），那么你也应该打开一个关于它的JPMML SkLearn问题。