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pythonscikit-learnmleap
Nastasia
Nastasia

Reputation: 667

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

I'm facing an issue with MLeap 0.16 and Python 3 when I try serialising a model. 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")

error:

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

Did anyone find a workaround?

Upvotes: 0

Views: 112

Answers (1)

Nastasia
Nastasia

Reputation: 667

I found the solution.

clf.mlinit(input_features="features", prediction_column="prediction")

was missing.

You can also use a pipeline to do that:

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")

Upvotes: 0

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