python - 序列化时使用 Skicit-learn 破坏 MLeap：对象没有属性“input_features”

Question

当我尝试序列化模型时，我遇到了 MLeap 0.16 和 Python 3 的问题。这是我的代码：

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")

错误：

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

有没有人找到解决方法？

Answer 1

我找到了解决方案。

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

失踪。

您还可以使用管道来执行此操作：

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")