Building a Simple Machine Learning SVM Classifier in MATLAB

This assignment focuses on the construction of a simple machine learning Support Vector Machine (SVM) classifier using MATLAB. It begins with an introduction to machine learning, discussing its implementation in various fields and its role in optimizing performance through data analysis. The document covers both supervised and unsupervised learning techniques, emphasizing the importance of algorithm selection in the machine learning process. It then delves into the specifics of decision trees and support vector machines, outlining their roles in classification. The practical section details the methodology for SVM design and modeling in MATLAB, including aims, results, and observations. The assignment also touches upon data mining techniques, knowledge discovery in databases, and tools used in data mining, providing a comprehensive overview of the machine learning landscape and its practical application in MATLAB.