Description

The transformer normalizes the value of the vector to [0,1] using the following formula:

x_scaled = (x - eMin) / (eMax - eMin) * (maxV - minV) + minV;

Parameters

Name Description Type Required？ Default Value
selectedCol Name of the selected column used for processing String ✓
min Lower bound after transformation. Double 0.0
max Upper bound after transformation. Double 1.0
outputCol Name of the output column String null

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], "vec" : data[:,1]})
  9. data = dataframeToOperator(df, schemaStr="col string, vec string",op_type="batch")
  10. res = VectorMinMaxScaler()\
  11.            .setSelectedCol("vec")
  12. res.fit(data).transform(data).collectToDataframe()

Result

col1 vec
a 0.5473107569721115,1.0
b 0.4850597609561753,0.08080808080808081
c 0.9965139442231076,0.0
d 0.0,1.0
a 0.5044820717131474,0.0
b 0.4865537848605578,0.08080808080808081
c 1.0,0.0