👉 Classification math is a branch of mathematics and machine learning that deals with assigning data points to predefined categories or classes based on their features. It involves using statistical models and algorithms to learn patterns from labeled training data, enabling the prediction of the category for new, unseen data. This process typically includes feature extraction, model training (often using techniques like logistic regression, decision trees, or neural networks), and evaluation metrics to measure performance. The core idea is to map input data into a probability distribution over classes, with the goal of maximizing accuracy and generalizability to new instances. Common applications include spam detection, image recognition, and sentiment analysis, where the classification task is to assign a label (e.g., "positive" or "negative") to a given input based on learned patterns.
