我用 Scikit-Learn 序列化一个模型:
#Generate data
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(100, 5), columns=['a', 'b', 'c', 'd', 'e'])
df["y"] = (df['a'] > 0.5).astype(int)
df.head()
from mleap.sklearn.ensemble.forest import RandomForestClassifier
forestModel = RandomForestClassifier()
forestModel.mlinit(input_features='a',
feature_names='a',
prediction_column='e_binary')
forestModel.fit(df[['a']], df[['y']])
forestModel.serialize_to_bundle("/dbfs/FileStore/tables/mleaptestmodelforest", "model.json")
当我尝试用 Pyspark 阅读它时:
from pyspark.ml.classification import RandomForestClassificationModel
model = RandomForestClassificationModel.deserializeFromBundle("file:/dbfs/FileStore/tables/mleaptestmodelforest")
我有这个错误:
java.nio.file.NoSuchFileException: /dbfs/FileStore/tables/mleaptestmodelforest/bundle.json
我没有“bundle.json”。
请问你能帮帮我吗?真的可以用 Scikit-Learn 序列化模型并用 Pyspark 反序列化它吗?