MinMaxScaler
Description
This API performs a normalization function using the maximum and minimum values of the data.
It has the same functionality as the sklearn.preprocessing.MinMaxScaler module, except that the maximum and minimum values must be provided directly.
Formula:
- X_std = (X - X.min) / (X.max - X.min)
- X_scaled = X_std * (max - min) + min
API module path
from api.v2.Preprocessing.MinMaxScaler import MinMaxScaler
Parameters
array
- Input time series data in array format.
- Example
- array = df.values
min
- Input the minimum value for each column.
- Example
- min = df.min().values
max
- Input the maximum value for each column.
- Example
- max = df.max().values
Example Sample Code (Python)
Results

Check the entire module code.
datahub/api/v2/Preprocessing/MinMaxScaler.py at main · machbase/datahub
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