Rule Learner is a machine learning tool designed to help business analysts extract classification rules from historical data without requiring extensive programming or data science expertise. By inputting historical data into two simple Excel tables, users can automatically generate decision tables that classify new data records based on past classifications. The generated rules are presented in a user-friendly Excel format, allowing for easy download and further analysis. Key Features and Functionality: - Automated Rule Generation: Utilizes machine learning algorithms to derive classification rules from historical data. - Excel Integration: Accepts input data in Excel tables and outputs the generated rules in an Excel decision table format. - Algorithm Selection: Offers the flexibility to choose from different machine learning algorithms to optimize rule accuracy. - User-Friendly Interface: Designed for business analysts, eliminating the need for advanced programming or data science skills. Primary Value and Problem Solved: Rule Learner empowers business analysts to harness the power of machine learning for data classification tasks without the steep learning curve typically associated with data science. By simplifying the process of rule extraction and providing results in familiar Excel formats, it enables organizations to make data-driven decisions more efficiently and accurately.