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Probabilistic Classification

Probabilistic classification in machine learning refers to classification models that predict a probability distribution over a set of classes, rather than just predicting the most likely class.

How Probabilistic Classification Works

These models, such as logistic regression and some neural networks, output probabilities for each class, which can be more informative than just a single class label, especially in cases where decision-making involves assessing risks and uncertainties.

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