Objectives¶
mean_squared_error (prediction, target) |
Mean Squared Error: |
root_mean_squared_error (prediction, target) |
Root Mean Squared Error: |
mean_absolute_error (prediction, target) |
Mean Absolute Error: |
binary_hinge_error (prediction, target) |
Binary Hinge Error: |
categorical_hinge_error (prediction, target) |
Categorical Hinge Error: |
binary_crossentropy_error (prediction, target) |
Binary Cross-entropy Error: |
categorical_crossentropy_error (prediction, ...) |
Categorical Cross-entropy Error: |
kullback_leibler_divergence (prediction, target) |
Kullback Leibler Divergence: |
Detailed description¶
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yadll.objectives.
mean_squared_error
(prediction, target)[source]¶ Mean Squared Error:
\[MSE_i = \frac{1}{n} \sum_{j}{(prediction_{i,j} - target_{i,j})^2}\]
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yadll.objectives.
root_mean_squared_error
(prediction, target)[source]¶ Root Mean Squared Error:
\[RMSE_i = \sqrt{\frac{1}{n} \sum_{j}{(target_{i,j} - prediction_{i,j})^2}}\]
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yadll.objectives.
mean_absolute_error
(prediction, target)[source]¶ Mean Absolute Error:
\[MAE_i = \frac{1}{n} \sum_{j}{|target_{i,j} - prediction_{i,j}|}\]
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yadll.objectives.
binary_hinge_error
(prediction, target)[source]¶ Binary Hinge Error:
\[BHE_i = \frac{1}{n} \sum_{j}{\max(0, 1 - target_{i,j} * prediction_{i,j})}\]
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yadll.objectives.
categorical_hinge_error
(prediction, target)[source]¶ Categorical Hinge Error:
\[CHE_i = \frac{1}{n} \sum_{j}{\max(1 - target_{i,j} * prediction_{i,j}, 0)}\]
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yadll.objectives.
binary_crossentropy_error
(prediction, target)[source]¶ Binary Cross-entropy Error:
\[BCE_i = - \frac{1}{n} \sum_{j}{(target_{i,j} * \log(prediction_{i,j}) - (1 - target_{i,j}) * \log(1 - prediction_{i,j}))}\]