td-classification-evaluator

What problem does it solve?

This skill automates the comprehensive evaluation of classification models, providing detailed metrics and diagnostics to assess performance and identify areas for improvement.

Core Features & Use Cases

• Automated Metrics Calculation: Generates accuracy, precision, recall, F1-score, and confusion matrices.
• Data Quality Checks: Validates data completeness, class distribution, and sample size.
• Diagnostic Queries: Provides insights into per-class performance and misclassification patterns.
• Use Case: After training a customer churn prediction model, use this skill to evaluate its performance against actual outcomes, ensuring it meets business requirements before deployment.

Quick Start

Evaluate the classification model performance on the table 'my_predictions' with actual labels in 'actual_col' and predicted labels in 'predicted_col'.