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 <[email protected]> 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
>
>
>
>
