Hi, The metadata for both LogisticRegression and MultilayerPerceptronClassifier follows:
{'ml_attr': {'vals': ['bad', 'good', '__unknown'], 'type': 'nominal', 'name': 'label'}} And, the label values are +-----+ |label| +-----+ | 0.0| | 1.0| +-----+ How come it throws *java.lang.IllegalArgumentException*:*requirement failed: OneHotEncoderModel expected 2 categorical values for input column label, but the input column had metadata specifying 3 values.'* in MultilayerPerceptronClassifier and not LogisticRegression. How can I resolve this? Regards, Mina On Tue, Nov 5, 2019 at 3:55 PM Mina Aslani <aslanim...@gmail.com> wrote: > Hi, > > I am getting the following exception when I am > using OneHotEncoderEstimator with MultilayerPerceptronClassifier in > Pyspark. (using version 2.4.4) > > *'requirement failed: OneHotEncoderModel expected x categorical values for > input column label, but the input column had metadata specifying n values.'* > > Using LogisticRegression, RandomForestClassifier or LinearRegression works > fine for the same data and OneHotEncoderEstimator. > > Any insight on how to resolve this? > > Regards, > Mina > > > >