What types of regression models can this skill handle?

The skill supports various models including linear and polynomial regression, selecting the most appropriate fit based on your specific dataset and requirements.

Can I use this skill for predictive forecasting?

Yes, the primary purpose of this skill is to build models that can predict future values based on existing historical data patterns.

Does it provide statistical validation for the models?

Absolutely. The tool validates generated models and provides key performance metrics such as R-squared and Root Mean Square Error (RMSE) to ensure reliability.

Do I need to clean my data before using this skill?

While the skill analyzes data structure, it is a best practice to ensure your data is clean and preprocessed to achieve the most accurate regression results.

Regression Analysis Tool

Name: Regression Analysis Tool
Author: jeremylongshore

byjeremylongshore

•

884

Data Science & ML

Performs advanced regression modeling and data analysis to uncover variable relationships and predict future trends.

About

This skill empowers Claude to act as a data scientist by automating the regression analysis process. It leverages the regression-analysis-tool plugin to ingest datasets, select optimal models—such as linear or polynomial regression—and validate them using standard metrics like R-squared and RMSE. Whether you are predicting market trends, housing prices, or identifying correlations in scientific data, this skill provides a structured approach to predictive modeling and statistical insight directly within your terminal.

Key Features

Predictive modeling for accurate future value forecasting
Trend visualization support and mathematical equation reporting
884 GitHub stars
Automated regression model generation including linear and polynomial types
In-depth data structure analysis to identify variable relationships
Comprehensive performance reporting with R-squared and RMSE metrics

Use Cases

Determining the statistical correlation between independent and dependent variables in research
Analyzing historical sales data to forecast future quarterly performance
Predicting real estate prices based on property features like square footage

About

Key Features

Predictive modeling for accurate future value forecasting
Trend visualization support and mathematical equation reporting
884 GitHub stars
Automated regression model generation including linear and polynomial types
In-depth data structure analysis to identify variable relationships
Comprehensive performance reporting with R-squared and RMSE metrics

Use Cases

Determining the statistical correlation between independent and dependent variables in research
Analyzing historical sales data to forecast future quarterly performance
Predicting real estate prices based on property features like square footage