Description

Chi-square test is chi-square independence test. Chi-square independence test is to test whether two factors affect each other. Its zero hypothesis is that the two factors are independent of each other. More information on chi-square test: http://en.wikipedia.org/wiki/Chi-squared_test

Parameters

Name Description Type Required？ Default Value
labelCol Name of the label column in the input table String ✓
selectedCols Names of the columns used for processing String[] ✓

Script Example

Script

  1. data = np.array([
  2.             ['a1','b1','c1'],
  3.             ['a1','b2','c1'],
  4.             ['a1','b1','c2'],
  5.             ['a2','b1','c1'],
  6.             ['a2','b2','c2'],
  7.             ['a2', 'b1','c1']])
  9. df = pd.DataFrame({"x1": data[:, 0], "x2": data[:, 1], "x3": data[:, 2]})
  10. source = dataframeToOperator(df, schemaStr='x1 string, x2 string, x3 string', op_type='batch')
  12. chisqTest = ChiSquareTestBatchOp()\
  13.             .setSelectedCols(["x1","x2"])\
  14.             .setLabelCol("x3")
  16. source.link(chisqTest).print()

Result

col chi2_result
x1 {“comment”:”pearson test”,”df”:1.0,”p”:1.0,”value”:0.0}
x2 {“comment”:”pearson test”,”df”:1.0,”p”:0.5402913746074196,”value”:0.37500000000000006}