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Message definition (Softmax Function)

The '''softmax function''' (also called the '''normalized exponential function''') is a mathematical function that converts a vector of real numbers ('''{{Term|logits}}''') into a probability distribution. It is the standard output {{Term|activation function|activation}} for multi-class classification in neural networks and plays a central role in models ranging from {{Term|logistic regression}} to large language models.

The softmax function (also called the normalized exponential function) is a mathematical function that converts a vector of real numbers (logits) into a probability distribution. It is the standard output activation for multi-class classification in neural networks and plays a central role in models ranging from logistic regression to large language models.

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	The '''softmax function''' (also called the '''normalized exponential function''') is a mathematical function that converts a vector of real numbers ('''logits''') into a probability distribution. It is the standard output activation for multi-class classification in neural networks and plays a central role in models ranging from logistic regression to large language models.		The '''softmax function''' (also called the '''normalized exponential function''') is a mathematical function that converts a vector of real numbers ('''{{Term\|logits}}''') into a probability distribution. It is the standard output {{Term\|activation function\|activation}} for multi-class classification in neural networks and plays a central role in models ranging from {{Term\|logistic regression}} to large language models.