Esempio n. 1
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def poisson(y_true, y_pred):
    return K.mean(y_pred - y_true * K.log(y_pred + K.epsilon()), axis=-1)
Esempio n. 2
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def mean_squared_logarithmic_error(y_true, y_pred):
    first_log = K.log(K.clip(y_pred, K.epsilon(), np.inf) + 1.)
    second_log = K.log(K.clip(y_true, K.epsilon(), np.inf) + 1.)
    return K.mean(K.square(first_log - second_log), axis=-1)
Esempio n. 3
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def kl_divergence(p, p_hat):
    return p_hat - p + p * K.log(p / p_hat)
Esempio n. 4
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def poisson(y_true, y_pred):
    return K.mean(y_pred - y_true * K.log(y_pred + K.epsilon()), axis=-1)
Esempio n. 5
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def mean_squared_logarithmic_error(y_true, y_pred):
    first_log = K.log(K.clip(y_pred, K.epsilon(), np.inf) + 1.)
    second_log = K.log(K.clip(y_true, K.epsilon(), np.inf) + 1.)
    return K.mean(K.square(first_log - second_log), axis=-1)
Esempio n. 6
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def kl_divergence(p, p_hat):
    return p_hat - p + p * K.log(p / p_hat)