huaxingao opened a new pull request #27623: [SPARK-30867][ML] Add 
FValueRegressionTest
URL: https://github.com/apache/spark/pull/27623
 
 
   
   
   ### What changes were proposed in this pull request?
   This is the very first PR for supporting continuous distribution features 
selectors.
   It adds the algorithm to compute fvalue for continuous features and 
continuous labels. This algorithm will be used for FValueRegressionSelector.
   
   
   ### Why are the changes needed?
   Current Spark only supports the selection of categorical features, while 
there are many requirements for the selection of continuous distribution 
features.
   
   I will add two new selectors:
   
   1. FValueRegressionSelector for continuous features and continuous labels.
   2. ANOVAFValueClassificationSelector for continuous features and categorical 
labels.
   
   I will use subtasks to add these two selectors:
   
   add FValueRegressionSelector on scala side
   
   - add FValueRegressionTest, this contains the algorithm to compute FValue
   - add FValueRegressionSelector using the above algorithm
   - add a common Selector, make FValueRegressionSelector  and ChisqSelector to 
extend common selector
   
   add FValueRegressionSelector on python side
   add samples and doc
   do the same for ANOVAFValueClassificationSelector
   
   
   ### Does this PR introduce any user-facing change?
   Yes. 
   ```
   /**
    * @param dataset  DataFrame of continuous labels and continuous features.
    * @param featuresCol  Name of features column in dataset, of type `Vector` 
(`VectorUDT`)
    * @param labelCol  Name of label column in dataset, of any numerical type
    * @return Array containing the SelectionTestResult for every feature 
against the label.
    */
   SelectionTest.fValueRegressionTest(dataset: Dataset[_], featuresCol: String, 
labelCol: String)
   ```
   
     
   
   
   ### How was this patch tested?
   Add Unit test.
   

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