research-ml-classical

What problem does it solve?

This Skill provides a comprehensive toolkit for classical machine learning tasks, simplifying the process of building, understanding, and visualizing ML models.

Core Features & Use Cases

• Model Training: Supports supervised (classification, regression) and unsupervised (clustering, dimensionality reduction) learning.
• Model Interpretation: Integrates SHAP for understanding feature importance and model behavior.
• Data Visualization: Utilizes UMAP for visualizing high-dimensional data.
• Use Case: Analyze customer data to predict churn (classification), optimize product recommendations (regression), or segment users into distinct groups (clustering).

Quick Start

Use the research-ml-classical skill to train a random forest classifier on your dataset.