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| ``mx.symbol.LinearRegressionOutput`` |
| ======================================================================== |
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| Description |
| ---------------------- |
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| Computes and optimizes for squared loss during backward propagation. |
| Just outputs ``data`` during forward propagation. |
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| If :math:`\hat{y}_i` is the predicted value of the i-th sample, and :math:`y_i` is the corresponding target value, |
| then the squared loss estimated over :math:`n` samples is defined as |
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| :math:`\text{SquaredLoss}(\textbf{Y}, \hat{\textbf{Y}} ) = \frac{1}{n} \sum_{i=0}^{n-1} \lVert \textbf{y}_i - \hat{\textbf{y}}_i \rVert_2` |
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| .. note:: Use the LinearRegressionOutput as the final output layer of a net. |
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| The storage type of ``label`` can be ``default`` or ``csr`` |
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| - LinearRegressionOutput(default, default) = default |
| - LinearRegressionOutput(default, csr) = default |
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| By default, gradients of this loss function are scaled by factor `1/m`, where m is the number of regression outputs of a training example. |
| The parameter `grad_scale` can be used to change this scale to `grad_scale/m`. |
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| Usage |
| ---------- |
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| .. code:: r |
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| mx.symbol.LinearRegressionOutput(...) |
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| Arguments |
| ------------------ |
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| +----------------------------------------+------------------------------------------------------------+ |
| | Argument | Description | |
| +========================================+============================================================+ |
| | ``data`` | NDArray-or-Symbol. | |
| | | | |
| | | Input data to the function. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``label`` | NDArray-or-Symbol. | |
| | | | |
| | | Input label to the function. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``grad.scale`` | float, optional, default=1. | |
| | | | |
| | | Scale the gradient by a float factor | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``name`` | string, optional. | |
| | | | |
| | | Name of the resulting symbol. | |
| +----------------------------------------+------------------------------------------------------------+ |
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| Value |
| ---------- |
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| ``out`` The result mx.symbol |
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| Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/regression_output.cc#L92 |
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