Classification

Classification is a supervised learning technique in machine learning where the objective is to predict the categorical label of new observations based on past data. It involves training a model on a labeled dataset, where each instance is associated with a category or class. The model learns to identify patterns and relationships within the data, allowing it to classify unseen instances into predefined categories. Common algorithms used for classification include decision trees, support vector machines, and neural networks. This technique is widely used in various applications such as spam detection, sentiment analysis, and medical diagnosis.