[jira] [Commented] (SPARK-12331) R^2 for regression through the origin
[ https://issues.apache.org/jira/browse/SPARK-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15066898#comment-15066898 ] Apache Spark commented on SPARK-12331: -- User 'iyounus' has created a pull request for this issue: https://github.com/apache/spark/pull/10384 > R^2 for regression through the origin > - > > Key: SPARK-12331 > URL: https://issues.apache.org/jira/browse/SPARK-12331 > Project: Spark > Issue Type: Improvement > Components: ML >Reporter: Imran Younus >Priority: Minor > > The value of R^2 (coefficient of determination) obtained from > LinearRegressionModel is not consistent with R and statsmodels when the > fitIntercept is false i.e., regression through the origin. In this case, both > R and statsmodels use the definition of R^2 given by eq(4') in the following > review paper: > https://online.stat.psu.edu/~ajw13/stat501/SpecialTopics/Reg_thru_origin.pdf > Here is the definition from this paper: > R^2 = \sum(\hat( y)_i^2)/\sum(y_i^2) > The paper also describes why this should be the case. I've double checked > that the value of R^2 from statsmodels and R are consistent with this > definition. On the other hand, scikit-learn doesn't use the above definition. > I would recommend using the above definition in Spark. -- 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] [Commented] (SPARK-12331) R^2 for regression through the origin
[ https://issues.apache.org/jira/browse/SPARK-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15061039#comment-15061039 ] DB Tsai commented on SPARK-12331: - +1 PR is welcome. Thanks. > R^2 for regression through the origin > - > > Key: SPARK-12331 > URL: https://issues.apache.org/jira/browse/SPARK-12331 > Project: Spark > Issue Type: Improvement > Components: ML >Reporter: Imran Younus >Priority: Minor > > The value of R^2 (coefficient of determination) obtained from > LinearRegressionModel is not consistent with R and statsmodels when the > fitIntercept is false i.e., regression through the origin. In this case, both > R and statsmodels use the definition of R^2 given by eq(4') in the following > review paper: > https://online.stat.psu.edu/~ajw13/stat501/SpecialTopics/Reg_thru_origin.pdf > Here is the definition from this paper: > R^2 = \sum(\hat( y)_i^2)/\sum(y_i^2) > The paper also describes why this should be the case. I've double checked > that the value of R^2 from statsmodels and R are consistent with this > definition. On the other hand, scikit-learn doesn't use the above definition. > I would recommend using the above definition in Spark. -- 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] [Commented] (SPARK-12331) R^2 for regression through the origin
[ https://issues.apache.org/jira/browse/SPARK-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15060875#comment-15060875 ] Joseph K. Bradley commented on SPARK-12331: --- +1 for this change based on the description (though I haven't checked the code & references myself). CCing [~dbtsai] It'd be great to add a unit test comparing with R results on the same data. > R^2 for regression through the origin > - > > Key: SPARK-12331 > URL: https://issues.apache.org/jira/browse/SPARK-12331 > Project: Spark > Issue Type: Improvement > Components: ML >Reporter: Imran Younus >Priority: Minor > > The value of R^2 (coefficient of determination) obtained from > LinearRegressionModel is not consistent with R and statsmodels when the > fitIntercept is false i.e., regression through the origin. In this case, both > R and statsmodels use the definition of R^2 given by eq(4') in the following > review paper: > https://online.stat.psu.edu/~ajw13/stat501/SpecialTopics/Reg_thru_origin.pdf > Here is the definition from this paper: > R^2 = \sum(\hat( y)_i^2)/\sum(y_i^2) > The paper also describes why this should be the case. I've double checked > that the value of R^2 from statsmodels and R are consistent with this > definition. On the other hand, scikit-learn doesn't use the above definition. > I would recommend using the above definition in Spark. -- 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] [Commented] (SPARK-12331) R^2 for regression through the origin
[ https://issues.apache.org/jira/browse/SPARK-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15058439#comment-15058439 ] Imran Younus commented on SPARK-12331: -- Sure, I can take care of this. > R^2 for regression through the origin > - > > Key: SPARK-12331 > URL: https://issues.apache.org/jira/browse/SPARK-12331 > Project: Spark > Issue Type: Improvement > Components: ML >Reporter: Imran Younus >Priority: Minor > > The value of R^2 (coefficient of determination) obtained from > LinearRegressionModel is not consistent with R and statsmodels when the > fitIntercept is false i.e., regression through the origin. In this case, both > R and statsmodels use the definition of R^2 given by eq(4') in the following > review paper: > https://online.stat.psu.edu/~ajw13/stat501/SpecialTopics/Reg_thru_origin.pdf > Here is the definition from this paper: > R^2 = \sum(\hat( y)_i^2)/\sum(y_i^2) > The paper also describes why this should be the case. I've double checked > that the value of R^2 from statsmodels and R are consistent with this > definition. On the other hand, scikit-learn doesn't use the above definition. > I would recommend using the above definition in Spark. -- 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] [Commented] (SPARK-12331) R^2 for regression through the origin
[ https://issues.apache.org/jira/browse/SPARK-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15057863#comment-15057863 ] Sean Owen commented on SPARK-12331: --- I'd support this change, if you're willing to do the legwork and create a PR and add a few tests for this behavior vs R's output. > R^2 for regression through the origin > - > > Key: SPARK-12331 > URL: https://issues.apache.org/jira/browse/SPARK-12331 > Project: Spark > Issue Type: Improvement > Components: ML >Reporter: Imran Younus >Priority: Minor > > The value of R^2 (coefficient of determination) obtained from > LinearRegressionModel is not consistent with R and statsmodels when the > fitIntercept is false i.e., regression through the origin. In this case, both > R and statsmodels use the definition of R^2 given by eq(4') in the following > review paper: > https://online.stat.psu.edu/~ajw13/stat501/SpecialTopics/Reg_thru_origin.pdf > Here is the definition from this paper: > R^2 = \sum(\hat( y)_i^2)/\sum(y_i^2) > The paper also describes why this should be the case. I've double checked > that the value of R^2 from statsmodels and R are consistent with this > definition. On the other hand, scikit-learn doesn't use the above definition. > I would recommend using the above definition in Spark. -- 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
