softmax

scikitplot.utils.helpers.softmax(x)

Compute the softmax function for each row of the input array x.

The softmax function is defined as:

softmax(x) = exp(x) / sum(exp(x))

This implementation is numerically stable by subtracting the max value in x before exponentiation to prevent overflow.

Parameters:

x (array-like) – Input array of shape (n_samples, n_features) for which to compute the softmax. Each row represents a different sample, and each column represents a different feature or class score.

Returns:

The softmax of each row in x, with the same shape as x.

Return type:

array-like