UC Irvine ML Repo Dataset Loader

A Streamlit interface for performing data analysis tasks such as hypothesis testing, linear regression modeling, and correlation analysis.

No datasets required, load and analyze any dataset from the UC Irvine Machine Learning Repository

Correlation Analysis:

Calculate correlation matrices using Pearson, Kendall, or Spearman methods.

Hypothesis Testing:

Perform one-sample t-tests, proportions z-tests, and confidence interval estimation.

Linear Regression Modeling:

The Hello World of ML. Build ordinary least squares (OLS), weighted least squares (WLS), and generalized least squares (GLS) regression models.

Installation

Before running the app, ensure you have Python installed on your system. You can install the required Python packages by running:

pip install -r requirements.txt

Usage

To launch the Streamlit app, run the following command in your terminal:

streamlit run app.py

This will open the app in your default web browser, where you can interact with the various features.

Contributing

Contributions are welcome! If you encounter any issues (there are a couple) or have suggestions, please feel free to open an issue or submit a pull request.