ncxlib
  • ⚡Welcome
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      • Overview
        • Neural Network
          • _compile
          • add_layer
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          • forward_propagate_all_no_save
          • back_propagation
          • train
          • predict
          • evaluate
          • save_model
          • load_model
        • Activation
          • ReLU
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        • Layer
          • InputLayer
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          • OutputLayer
        • LossFunction
          • MeanSquaredError
          • BinaryCrossEntropy
          • CategoricalCrossEntropy
        • Optimizer
          • SGD
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          • RMSProp
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        • Initializer
          • HeNormal
          • Zero
        • PreProcessor
          • OneHotEncoder
          • MinMaxScaler
          • Scaler
          • ImageRescaler
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        • DataLoader
          • CSVDataLoader
          • ImageDataLoader
        • Generators
          • random_array
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          • generate_training_data
        • Utils
          • train_test_split
          • k_fold_cross_validation
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  4. LossFunction

CategoricalCrossEntropy

class CategoricalCrossEntropy(LossFunction):
    
    @staticmethod
    def compute_loss(y_true: np.ndarray, y_pred: np.ndarray):
        epsilon = 1e-12
        y_pred = np.clip(y_pred, epsilon, 1. - epsilon)
        return -np.sum(y_true * np.log(y_pred), axis=1).mean()

    @staticmethod
    def compute_gradient(y_true: np.ndarray, y_pred: np.ndarray):
        epsilon = 1e-12
        y_pred = np.clip(y_pred, epsilon, 1. - epsilon)
        return -y_true / y_pred
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Last updated 7 months ago