imbalanced-classification

What problem does it solve?

The imbalanced-classification Skill unit helps to tackle the issue of class imbalance in classification tasks, which is a common challenge in machine learning.

Core Features & Use Cases

• Class Imbalance Handling: Offers strategies and techniques to manage and mitigate class imbalance in datasets.
• Use Case: Ideal for data scientists working on models that are heavily skewed towards one class, enhancing model accuracy and fairness.

Quick Start

Use the imbalanced-classification skill to apply the 'oversampling' technique to your dataset and balance class distribution before training your model.