Classification
Classification is a supervised learning technique in which an algorithm learns from labeled data to predict the class or category of new, unlabeled data. The goal of classification is to accurately assign new observations to previously defined categories or classes based on their features or attributes. Classification is widely used in various fields such as image recognition, natural language processing, and fraud detection. There are several algorithms used for classification such as decision trees, logistic regression, support vector machines, and k-nearest neighbors. The performance of a classification model is evaluated using metrics such as accuracy, precision, recall, and F1 score.
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