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https://issues.apache.org/jira/browse/SPARK-2515?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14073879#comment-14073879
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Doris Xin commented on SPARK-2515:
----------------------------------
Here's the proposed API for chi-squared tests (lives in
org.apache.spark.mllib.stat.Statistics):
{code}
def chiSquare(X: RDD[Vector], method: String = “pearson”): ChiSquareTestResult
def chiSquare(x: RDD[Double], y: RDD[Double], method: String = “pearson”):
ChiSquareTestResult
{code}
where ChiSquareTestResult <: TestResult looks like:
{code}
pValue: Double
df: Array[Int] //normally a single but need to be more for anova
statistic: Double
ChiSquareSummary <: Summary
{code}
So a couple points of discussion:
1. Of the many variants of the chi-squared test, what methods in addition to
"pearson" do we want to support (hopefully based on popular demand)?
http://en.wikipedia.org/wiki/Chi-squared_test
2. What special fields should ChiSquareSummary have?
> Hypothesis testing
> ------------------
>
> Key: SPARK-2515
> URL: https://issues.apache.org/jira/browse/SPARK-2515
> Project: Spark
> Issue Type: Sub-task
> Components: MLlib
> Reporter: Xiangrui Meng
> Assignee: Doris Xin
>
> Support common statistical tests in Spark MLlib.
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