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https://issues.apache.org/jira/browse/SPARK-17116?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Manoj Kumar updated SPARK-17116:
--------------------------------
Description:
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}
was:
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}
> 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}
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