Predictive Rule learning clearly explained (Data Mining)

Learn how to build Rule Based Models for Data Mining and Machine Learning. In this tutorial, we explain the Separate and Conquer strategy and how to use Pruning to avoid overfitting. In this video, we explore how to predict customer preferences using predictive rule learning (Data Mining), building on the previous discussions about subgroup discovery and descriptive rule learning. We use examples to illustrate how to create clear and understandable rules for prediction, introducing the Separate and Conquer algorithm. Methods to refine these rules, such as pruning and pre-pruning, are also covered. The content is based on a course in computational data analytics by Johannes FK at JKU. 00:00 Introduction to Predictive Rule Learning 00:39 Recap of Subgroup Discovery 02:34 How to Create Classification Rules 03:27 Applying the Rules to New Customers 04:26 The Separate and Conquer Algorithm 07:37 Pruning Rules to Prevent Overfitting 09:37 Conclusion and Credits