title: sklearn.preprocessing._data.MinMaxScaler is not a supported Transformer When the model is converted to PMML using sklearn2pmml
body: <pre><code>from sklearn.preprocessing import StandardScaler,MinMaxScaler
  from sklearn2pmml.pipeline import PMMLPipeline
  from sklearn.impute import SimpleImputer
  from sklearn_pandas import DataFrameMapper
  
  mapper = DataFrameMapper([
          (model_col,[SimpleImputer(strategy = "most_frequent"),MinMaxScaler()])
      ])
  
  clf = GradientBoostingClassifier(n_estimators=200,learning_rate=0.1,max_depth=5,random_state=10)
  gbdt_pipeline = PMMLPipeline([('mapper', mapper), ("classifier", clf)])
  
  sklearn2pmml(gbdt_pipeline,"gbdt.pmml",with_repr=True)
  </code></pre>
  
  <p>Convert to PMML to report an error. The error is as follows</p>
  
  <pre><code>Standard output is empty
  Standard error:
   28, 2020 4:04:05  org.jpmml.sklearn.Main run
  Ϣ: Parsing PKL..
   28, 2020 4:04:05  org.jpmml.sklearn.Main run
  Ϣ: Parsed PKL in 80 ms.
   28, 2020 4:04:05  org.jpmml.sklearn.Main run
  Ϣ: Converting..
   28, 2020 4:04:05  org.jpmml.sklearn.Main run
  : Failed to convert
  java.lang.IllegalArgumentException: The value object (Python class sklearn.preprocessing._data.MinMaxScaler) is not a supported Transformer
      at org.jpmml.sklearn.CastFunction.apply(CastFunction.java:43)
      at com.google.common.collect.Lists$TransformingRandomAccessList$1.transform(Lists.java:612)
      at com.google.common.collect.TransformedIterator.next(TransformedIterator.java:47)
      at sklearn_pandas.DataFrameMapper.initializeFeatures(DataFrameMapper.java:72)
      at sklearn.Initializer.encodeFeatures(Initializer.java:41)
      at sklearn.Transformer.updateAndEncodeFeatures(Transformer.java:85)
      at sklearn.pipeline.Pipeline.encodeFeatures(Pipeline.java:83)
      at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:203)
      at org.jpmml.sklearn.Main.run(Main.java:145)
      at org.jpmml.sklearn.Main.main(Main.java:94)
  Caused by: java.lang.ClassCastException: Cannot cast net.razorvine.pickle.objects.ClassDict to sklearn.Transformer
      at java.lang.Class.cast(Unknown Source)
      at org.jpmml.sklearn.CastFunction.apply(CastFunction.java:41)
      ... 9 more
  </code></pre>
  
  <p>The scikit-learn I used is 0.22.2, and when I use version 0.21, there are no errors
  Thanks for any help!</p>