Dear all, I want to update my code of pyspark. In the pyspark, it must put the base model in a pipeline, the office demo of pipeline use the LogistictRegression as an base model. However, it seems not be able to use XGboost model in the pipeline api. How can I use the pyspark like this:
from xgboost import XGBClassifier ... model = XGBClassifier() model.fit(X_train, y_train) pipeline = Pipeline(stages=[..., model, ...]) It is convenient to use the pipeline api, so can anybody give some advices? Thank you! Daniel -- Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/ --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
