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
data = np.array([["a", "10.0, 100"],\
["b", "-2.5, 9"],\
["c", "100.2, 1"],\
["d", "-99.9, 100"],\
["a", "1.4, 1"],\
["b", "-2.2, 9"],\
["c", "100.9, 1"]])
df = pd.DataFrame({"col" : data[:,0], "vec" : data[:,1]})
data = dataframeToOperator(df, schemaStr="col string, vec string",op_type="batch")
res = VectorMinMaxScaler()\
.setSelectedCol("vec")
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 |