Description

StandardScaler transforms a dataset, normalizing each feature to have unit standard deviation and/or zero mean.

Parameters

Name Description Type Required？ Default Value
selectedCol Name of the selected column used for processing String ✓
withMean Centers the data with mean before scaling. Boolean true
withStd Scales the data to unit standard deviation. true by default Boolean true

Script Example

Script

  1. data = np.array([["a", "10.0, 100"],\
  2.     ["b", "-2.5, 9"],\
  3.     ["c", "100.2, 1"],\
  4.     ["d", "-99.9, 100"],\
  5.     ["a", "1.4, 1"],\
  6.     ["b", "-2.2, 9"],\
  7.     ["c", "100.9, 1"]])
  8. df = pd.DataFrame({"col" : data[:,0], "vector" : data[:,1]})
  9. data = dataframeToOperator(df, schemaStr="col string, vector string",op_type="batch")
  10. dataStream = dataframeToOperator(df, schemaStr="col string, vector string",op_type="stream")
  11. trainOp = VectorStandardScalerTrainBatchOp().setSelectedCol("vector")
  12. model = trainOp.linkFrom(data)
  13. VectorStandardScalerPredictStreamOp(model).linkFrom(dataStream).print()
  14. StreamOperator.execute()

Result

col1 vec
a -0.07835182408093559,1.4595814453461897
c 1.2269606224811418,-0.6520885789229323
b -0.2549018445693762,-0.4814485769617911
a -0.20280511721213143,-0.6520885789229323
c 1.237090541689495,-0.6520885789229323
b -0.25924323851581327,-0.4814485769617911
d -1.6687491397923802,1.4595814453461897