Description
MinMaxScaler transforms a dataSet of rows, rescaling each feature
to a specific range [min, max). (often [0, 1]).
MinMaxScalerTrain will train a model.
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 |
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")
trainOp = VectorMinMaxScalerTrainBatchOp()\
.setSelectedCol("vec")
model = trainOp.linkFrom(data)
batchPredictOp = VectorMinMaxScalerPredictBatchOp()
batchPredictOp.linkFrom(model, 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 |