Softmax Function
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EasyNeural Networks
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GoogleWhy this matters:
Tests understanding of probability distributions in classification – essential for multi-class problems.
The softmax function converts a vector of real numbers into a probability distribution. Each output is in the range (0, 1) and the outputs sum to 1.
Examples
Input:
x = [1.0, 2.0, 3.0]
Output:
[0.09, 0.24, 0.67]
Explanation:
Larger values get higher probabilities, and sum of outputs = 1
Constraints
- Handle numerical stability (subtract max value)
- Output should satisfy sum of p_i = 1.0
- Works on 1D and 2D arrays
Tags
llmstransformersclassic-nlp