[SPARK-7159] Support multiclass logistic regression in spark.ml

• Type: New Feature
• Status: Resolved
• Priority: Critical
• Resolution: Fixed
• Fix Version/s: 2.1.0
• Component/s: ML
• Target Version/s: 2.1.0
• Assignee: Seth Hendrickson
• Reporter: Joseph K. Bradley
• Shepherd: DB Tsai
• Created: 27/Apr/15 04:21
• Updated: 25/Aug/16 17:51
• Resolved: 19/Aug/16 14:15

Description

This should be implemented by checking the input DataFrame's label column for feature metadata specifying the number of classes.

Issue Links

• Is contained by: SPARK-14377 Review spark.ml parity for classification, except trees
• is related to: SPARK-10523 SparkR formula syntax to turn strings/factors into numerics
• is related to: SPARK-16592 Improving ml.Logistic Regression on speed and scalability
• is related to: SPARK-17239 User guide for multiclass logistic regression in spark.ml
• relates to: SPARK-10179 LogisticRegressionWithSGD does not multiclass
• relates to: SPARK-17133 Improvements to linear methods in Spark
• links to: [Github] Pull Request #13796 (sethah)