SIT717 Enterprise Business Intelligence Project: Weka Data Analysis

This project explores data mining and machine learning techniques using the Weka software on a health news dataset. The assignment is divided into several practical sections, covering data pre-processing, data visualization, and dimension reduction. It delves into clustering algorithms, specifically K-Means, and classification algorithms like Naive Bayes. The project includes performance evaluation using Weka Experimenter and Knowledge Flow, time series prediction, text mining, and image analysis. The analysis involves the application of various data mining techniques to extract knowledge and insights from the provided dataset, with detailed explanations and demonstrations of each step. This assignment is a comprehensive exploration of data mining principles and their practical application in business intelligence, providing a hands-on experience with the Weka platform.