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
All Industrial IoT DataHub with data visualization and AI source - machbase/datahub

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