td-model-selection

What problem does it solve?

This skill automates the complex process of selecting the best forecasting model from a range of options, saving significant time and effort in data analysis and prediction tasks.

Core Features & Use Cases

• Automated Model Comparison: Analyzes various time series models (ARIMA, Exponential Smoothing, etc.) to identify the most suitable one.
• Performance Evaluation: Assesses models based on criteria like AIC, BIC, and cross-validation error.
• Use Case: A retail company wants to forecast sales for thousands of products. This skill can automatically analyze historical sales data for each product and recommend the best forecasting model, ensuring accurate predictions and optimized inventory management.

Quick Start

Use the td-model-selection skill to analyze time series table: my_database.sales_data with timestamp column and value columns.