public class ChiSqTest
extends Object
Vectors, whereas test of independence is conducted
 on an input of type Matrix in which independence between columns is assessed.
 We also provide a method for computing the chi-squared statistic between each feature and the
 label for an input RDD[LabeledPoint], return an Array[ChiSquaredTestResult] of size =
 number of features in the input RDD.
 
 Supported methods for goodness of fit: pearson (default)
 Supported methods for independence: pearson (default)
 
More information on Chi-squared test: http://en.wikipedia.org/wiki/Chi-squared_test
| Modifier and Type | Class and Description | 
|---|---|
| static class  | ChiSqTest.Methodparam:  name String name for the method. | 
| static class  | ChiSqTest.Method$ | 
| static class  | ChiSqTest.NullHypothesis$ | 
| Constructor and Description | 
|---|
| ChiSqTest() | 
| Modifier and Type | Method and Description | 
|---|---|
| static ChiSqTestResult | chiSquared(Vector observed,
          Vector expected,
          String methodName) | 
| static ChiSqTestResult[] | chiSquaredFeatures(RDD<LabeledPoint> data,
                  String methodName)Conduct Pearson's independence test for each feature against the label across the input RDD. | 
| static ChiSqTestResult | chiSquaredMatrix(Matrix counts,
                String methodName) | 
| static void | org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1) | 
| static org.slf4j.Logger | org$apache$spark$internal$Logging$$log_() | 
| static ChiSqTest.Method | PEARSON() | 
public static ChiSqTest.Method PEARSON()
public static ChiSqTestResult[] chiSquaredFeatures(RDD<LabeledPoint> data, String methodName)
data - (undocumented)methodName - (undocumented)public static ChiSqTestResult chiSquared(Vector observed, Vector expected, String methodName)
public static ChiSqTestResult chiSquaredMatrix(Matrix counts, String methodName)
public static org.slf4j.Logger org$apache$spark$internal$Logging$$log_()
public static void org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)