MLeap broken with Skicit-learn when serialising:I object has no attribute 'input_features'

[NastasiaSaby]

I'm facing an issue with MLeap 0.16 and Python 3.
Here is my code:

from mleap.sklearn.logistic import LogisticRegression
from sklearn.datasets import load_iris

X, y = load_iris(return_X_y=True)
clf = LogisticRegression(random_state=0).fit(X, y)

clf.serialize_to_bundle("path", "irismodel")

Here is my error:

AttributeError: 'LogisticRegression' object has no attribute 'input_features'

Let me know if you need more details.

Thank you.

[NastasiaSaby]

I found a solution. However, I don't know if it is the best way to do it.

from mleap.sklearn.logistic import LogisticRegression
from sklearn.datasets import load_iris
from mleap.sklearn.pipeline import Pipeline

X, y = load_iris(return_X_y=True)
logistic = LogisticRegression(random_state=0)
logistic.mlinit(input_features="features", prediction_column="prediction")
pipeline = Pipeline([("log", logistic)])
clf = pipeline.fit(X, y)

clf.mlinit()

clf.serialize_to_bundle("/dbfs/endpath", "model.json")

[ancasarb]

hey @NastasiaSaby

The solution seems fine to me.

I think

from mleap.sklearn.logistic import LogisticRegression
from sklearn.datasets import load_iris

X, y = load_iris(return_X_y=True)
clf = LogisticRegression(random_state=0).fit(X, y)

clf.serialize_to_bundle("path", "irismodel")

would also work if you add the clf.mlinit(input_features="features", prediction_column="prediction") for it.

Hope this helps, let me know if you have any other questions.

[NastasiaSaby]

@ancasarb I created a pull request for the documentation: combust/mleap-docs#24.