Module balancing

Data balancing utilities for handling imbalanced datasets

This module provides various strategies for balancing datasets to handle class imbalance problems in machine learning. It includes random oversampling, random undersampling, and SMOTE-like synthetic sample generation.

Enums

BalancingStrategy

Balancing strategies for handling imbalanced datasets

Functions

create_balanced_dataset

Creates a balanced dataset using the specified balancing strategy

generate_synthetic_samples

Generates synthetic samples using SMOTE-like interpolation

random_oversample

Performs random oversampling to balance class distribution

random_undersample

Performs random undersampling to balance class distribution