package mllib
RDD-based machine learning APIs (in maintenance mode).
The spark.mllib
package is in maintenance mode as of the Spark 2.0.0 release to encourage
migration to the DataFrame-based APIs under the org.apache.spark.ml package.
While in maintenance mode,
- no new features in the RDD-based
spark.mllib
package will be accepted, unless they block implementing new features in the DataFrame-basedspark.ml
package; - bug fixes in the RDD-based APIs will still be accepted.
The developers will continue adding more features to the DataFrame-based APIs in the 2.x series to reach feature parity with the RDD-based APIs. And once we reach feature parity, this package will be deprecated.
- Source
- package.scala
- See also
SPARK-4591 to track the progress of feature parity
Package Members
- package classification
- package clustering
- package evaluation
- package feature
- package fpm
- package linalg
- package optimization
- package pmml
- package random
- package rdd
- package recommendation
- package regression
- package stat
- package tree
This package contains the default implementation of the decision tree algorithm, which supports:
This package contains the default implementation of the decision tree algorithm, which supports:
- binary classification,
- regression,
- information loss calculation with entropy and Gini for classification and variance for regression,
- both continuous and categorical features.
- package util
Type Members
- class JavaPackage extends AnyRef
A dummy class as a workaround to show the package doc of
spark.mllib
in generated Java API docs.A dummy class as a workaround to show the package doc of
spark.mllib
in generated Java API docs.- Annotations
- @AlphaComponent()
- See also