Classification Models
Classification models are a type of machine learning algorithm that is used to predict the categorical class labels of new instances based on past observations. These models are trained on a labeled dataset, where the class labels are known, and then used to classify new, unseen data. The goal of classification is to accurately predict the class label of new instances based on the patterns and relationships learned from the training data. There are several types of classification models, including decision trees, logistic regression, support vector machines, and neural networks.
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