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Posted to issues@spark.apache.org by "Burak Yavuz (JIRA)" <ji...@apache.org> on 2015/05/08 21:36:00 UTC
[jira] [Updated] (SPARK-7492) Convert LocalDataFrame to LocalMatrix
[ https://issues.apache.org/jira/browse/SPARK-7492?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Burak Yavuz updated SPARK-7492:
-------------------------------
Description:
Having a method like,
{code: java}
Matrices.fromDataFrame(df)
{code}
would provide users the ability to perform feature selection with DataFrames.
Users will be able to chain operations like below:
{code: java}
import org.apache.spark.mllib.linalg.Matrices
import org.apache.spark.mllib.stat.Statistics
import org.apache.spark.sql.DataFrame
val df = ... // the DataFrame
val contingencyTable = df.stat.crosstab(col1, col2)
val ct = Matrices.fromDataFrame(contingencyTable)
val result: ChiSqTestResult = Statistics.chiSqTest(ct)
{code}
was:
Having a method like,
{code: scala}
Matrices.fromDataFrame(df)
{code}
would provide users the ability to perform feature selection with DataFrames.
Users will be able to chain operations like below:
{code: scala}
import org.apache.spark.mllib.linalg.Matrices
import org.apache.spark.mllib.stat.Statistics
import org.apache.spark.sql.DataFrame
val df = ... // the DataFrame
val contingencyTable = df.stat.crosstab(col1, col2)
val ct = Matrices.fromDataFrame(contingencyTable)
val result: ChiSqTestResult = Statistics.chiSqTest(ct)
{code}
> Convert LocalDataFrame to LocalMatrix
> -------------------------------------
>
> Key: SPARK-7492
> URL: https://issues.apache.org/jira/browse/SPARK-7492
> Project: Spark
> Issue Type: New Feature
> Components: MLlib, SQL
> Reporter: Burak Yavuz
>
> Having a method like,
> {code: java}
> Matrices.fromDataFrame(df)
> {code}
> would provide users the ability to perform feature selection with DataFrames.
> Users will be able to chain operations like below:
> {code: java}
> import org.apache.spark.mllib.linalg.Matrices
> import org.apache.spark.mllib.stat.Statistics
> import org.apache.spark.sql.DataFrame
> val df = ... // the DataFrame
> val contingencyTable = df.stat.crosstab(col1, col2)
> val ct = Matrices.fromDataFrame(contingencyTable)
> val result: ChiSqTestResult = Statistics.chiSqTest(ct)
> {code}
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