Classification Models

Classification models are a cornerstone of machine learning, where they are tasked with the crucial function of sorting input data into predefined categories. These models analyze the features of input data and make predictions about which category or class the data belongs to. The process involves learning from a dataset that has already been labeled, known as the training set, which allows the model to understand how different features correlate with specific categories. Once trained, the model can then apply this learned knowledge to new, unseen data, categorizing it into the classes it has learned about. Classification models are widely applied in various fields such as email filtering (spam or non-spam), medical diagnosis (diseased or healthy), and financial analysis (fraudulent or legitimate transactions), showcasing their versatility and importance in data-driven decision-making.