Function categorical_accuracy 

pub fn categorical_accuracy<F: Float + Debug>(
    predictions: &Array<F, Ix2>,
    targets: &Array<F, Ix2>,
) -> Result<F>

Calculate the categorical accuracy between predictions and targets

Arguments

• predictions - Predicted class probabilities (each row sums to 1)
• targets - One-hot encoded target classes (each row has a single 1)

Returns

• The accuracy (proportion of correct predictions)

Examples

use scirs2_neural::utils::categorical_accuracy;
use scirs2_core::ndarray::arr2;

let predictions = arr2(&[
    [0.7f64, 0.2, 0.1],  // Predicted class: 0
    [0.3f64, 0.6, 0.1],  // Predicted class: 1
    [0.2f64, 0.3, 0.5]   // Predicted class: 2
]);
let targets = arr2(&[
    [1.0f64, 0.0, 0.0],  // True class: 0
    [0.0f64, 1.0, 0.0],  // True class: 1
    [0.0f64, 0.0, 1.0]   // True class: 2
]);
let accuracy = categorical_accuracy(&predictions, &targets).unwrap();
assert_eq!(accuracy, 1.0f64); // All predictions are correct