Classification Model
A classification model is a type of machine learning model that is used to predict the categorical class labels of new instances based on past observations. It is a supervised learning technique that involves training a model on a labeled dataset, where the class labels are known, and then using the trained model to predict the class labels of new, unseen instances. The goal of a classification model is to accurately classify new instances into one of the predefined classes. There are various types of classification models, including decision trees, logistic regression, support vector machines, and neural networks.
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