Description

Normalizer is a Transformer which transforms a dataset of Vector rows, normalizing each Vector to have unit norm. It takes parameter p, which specifies the p-norm used for normalization. This normalization can help standardize your input data and improve the behavior of learning algorithms.

Parameters

Name Description Type Required？ Default Value
p number of degree. Double 2.0
selectedCol Name of the selected column used for processing String ✓
outputCol Name of the output column String null
reservedCols Names of the columns to be retained in the output table String[] null

Script Example

Script

  1. data = np.array([["1:3,2:4,4:7", 1],\
  2.     ["0:3,5:5", 3],\
  3.     ["2:4,4:5", 4]])
  4. df = pd.DataFrame({"vec" : data[:,0], "id" : data[:,1]})
  5. data = dataframeToOperator(df, schemaStr="vec string, id bigint",op_type="batch")
  6. VectorNormalizeBatchOp().setSelectedCol("vec").setOutputCol("vec_norm").linkFrom(data).collectToDataframe()

Result

vec id vec_norm
1:3,2:4,4:7 1 1:0.34874291623145787 2:0.46499055497527714 4:0.813733471206735
0:3,5:5 3 0:0.5144957554275265 5:0.8574929257125441
2:4,4:5 4 2:0.6246950475544243 4:0.7808688094430304