[jira] [Assigned] (SPARK-17116) Allow params to be a {string, value} dict at fit time
[ https://issues.apache.org/jira/browse/SPARK-17116?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-17116: Assignee: Apache Spark > Allow params to be a {string, value} dict at fit time > - > > Key: SPARK-17116 > URL: https://issues.apache.org/jira/browse/SPARK-17116 > Project: Spark > Issue Type: Improvement > Components: ML, PySpark >Reporter: Manoj Kumar >Assignee: Apache Spark >Priority: Minor > > Currently, it is possible to override the default params set at constructor > time by supplying a ParamMap which is essentially a (Param: value) dict. > Looking at the codebase, it should be trivial to extend this to a (string, > value) representation. > {code} > # This hints that the maxiter param of the lr instance is modified in-place > lr = LogisticRegression(maxIter=10, regParam=0.01) > lr.fit(dataset, {lr.maxIter: 20}) > # This seems more natural. > lr.fit(dataset, {"maxIter": 20}) > {code} -- 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] [Assigned] (SPARK-17116) Allow params to be a {string, value} dict at fit time
[ https://issues.apache.org/jira/browse/SPARK-17116?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-17116: Assignee: (was: Apache Spark) > Allow params to be a {string, value} dict at fit time > - > > Key: SPARK-17116 > URL: https://issues.apache.org/jira/browse/SPARK-17116 > Project: Spark > Issue Type: Improvement > Components: ML, PySpark >Reporter: Manoj Kumar >Priority: Minor > > Currently, it is possible to override the default params set at constructor > time by supplying a ParamMap which is essentially a (Param: value) dict. > Looking at the codebase, it should be trivial to extend this to a (string, > value) representation. > {code} > # This hints that the maxiter param of the lr instance is modified in-place > lr = LogisticRegression(maxIter=10, regParam=0.01) > lr.fit(dataset, {lr.maxIter: 20}) > # This seems more natural. > lr.fit(dataset, {"maxIter": 20}) > {code} -- 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