[jira] [Updated] (SPARK-5016) GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
[ https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-5016: - Assignee: Feynman Liang > GaussianMixtureEM should distribute matrix inverse for large numFeatures, k > --- > > Key: SPARK-5016 > URL: https://issues.apache.org/jira/browse/SPARK-5016 > Project: Spark > Issue Type: Improvement > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Joseph K. Bradley >Assignee: Feynman Liang > Labels: clustering > > If numFeatures or k are large, GMM EM should distribute the matrix inverse > computation for Gaussian initialization. -- 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-5016) GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
[ https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-5016: - Target Version/s: 1.5.0 > GaussianMixtureEM should distribute matrix inverse for large numFeatures, k > --- > > Key: SPARK-5016 > URL: https://issues.apache.org/jira/browse/SPARK-5016 > Project: Spark > Issue Type: Improvement > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Joseph K. Bradley >Assignee: Feynman Liang > Labels: clustering > > If numFeatures or k are large, GMM EM should distribute the matrix inverse > computation for Gaussian initialization. -- 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-5016) GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
[ https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-5016: - Labels: clustering (was: ) > GaussianMixtureEM should distribute matrix inverse for large numFeatures, k > --- > > Key: SPARK-5016 > URL: https://issues.apache.org/jira/browse/SPARK-5016 > Project: Spark > Issue Type: Improvement > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Joseph K. Bradley > Labels: clustering > > If numFeatures or k are large, GMM EM should distribute the matrix inverse > computation for Gaussian initialization. -- 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-5016) GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
[ https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen updated SPARK-5016: - Target Version/s: (was: 1.3.0) > GaussianMixtureEM should distribute matrix inverse for large numFeatures, k > --- > > Key: SPARK-5016 > URL: https://issues.apache.org/jira/browse/SPARK-5016 > Project: Spark > Issue Type: Improvement > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Joseph K. Bradley > Labels: clustering > > If numFeatures or k are large, GMM EM should distribute the matrix inverse > computation for Gaussian initialization. -- 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-5016) GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
[ https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng updated SPARK-5016: - Shepherd: Xiangrui Meng > GaussianMixtureEM should distribute matrix inverse for large numFeatures, k > --- > > Key: SPARK-5016 > URL: https://issues.apache.org/jira/browse/SPARK-5016 > Project: Spark > Issue Type: Improvement > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Joseph K. Bradley >Assignee: Feynman Liang > Labels: clustering > > If numFeatures or k are large, GMM EM should distribute the matrix inverse > computation for Gaussian initialization. -- 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
