[jira] [Updated] (SPARK-4111) [MLlib] Implement regression model evaluation metrics
[ https://issues.apache.org/jira/browse/SPARK-4111?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-4111: - Assignee: Yanbo Liang [MLlib] Implement regression model evaluation metrics - Key: SPARK-4111 URL: https://issues.apache.org/jira/browse/SPARK-4111 Project: Spark Issue Type: New Feature Components: MLlib Affects Versions: 1.2.0 Reporter: Yanbo Liang Assignee: Yanbo Liang Fix For: 1.2.0 Supervised machine learning include classification and regression. There is classification metrics (BinaryClassificationMetrics) in MLlib, we also need regression metrics to evaluate the regression model and tunning parameter. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-4111) [MLlib] Implement regression model evaluation metrics
[ https://issues.apache.org/jira/browse/SPARK-4111?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Yanbo Liang updated SPARK-4111: --- Summary: [MLlib] Implement regression model evaluation metrics (was: Implement regression model evaluation metrics) [MLlib] Implement regression model evaluation metrics - Key: SPARK-4111 URL: https://issues.apache.org/jira/browse/SPARK-4111 Project: Spark Issue Type: New Feature Components: MLlib Affects Versions: 1.2.0 Reporter: Yanbo Liang Supervised machine learning include classification and regression. There is classification metrics (BinaryClassificationMetrics) in MLlib, we also need regression metrics to evaluate the regression model and tunning parameter. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
