GitHub
deepbox/preprocess

Scalers

Scaling, normalization, and power or quantile transforms for numerical features.
Scaling

MaxAbsScaler

Scale features by maximum absolute value.

MinMaxScaler

Scale features to a range [min, max].

Normalizer

Normalize samples to unit norm.

PowerTransformer

Apply power transform to make data more Gaussian-like.

QuantileTransformer

Transform features using quantiles.

RobustScaler

Robust scaler using median and IQR.

StandardScaler

Standardize features by removing mean and scaling to unit variance.

preprocess-scalers.ts
import {  MinMaxScaler,  RobustScaler,  StandardScaler,} from "deepbox/preprocess";import { tensor } from "deepbox/ndarray";const X = tensor([[1, 10], [2, 20], [3, 30]]);console.log(new StandardScaler().fit(X).transform(X).toString());console.log(new MinMaxScaler().fit(X).transform(X).toString());console.log(new RobustScaler().fit(X).transform(X).toString());