👉 Classification computing is a subset of machine learning focused on categorizing data into predefined classes or labels. It involves training algorithms to distinguish between different categories based on input features, often using supervised learning techniques where the model learns from labeled examples. The goal is to map input data to the correct class based on patterns and relationships identified during training. Common applications include spam detection in emails, image recognition (e.g., identifying objects in photos), and medical diagnosis (classifying diseases based on symptoms). Classification models can range from simple linear classifiers like logistic regression to complex neural networks, each with varying levels of complexity and accuracy. The performance of these models is typically evaluated using metrics like accuracy, precision, recall, and F1-score.
