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https://issues.apache.org/jira/browse/SINGA-176?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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wangwei resolved SINGA-176.
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Resolution: Fixed
> Add loss and metric base classes
> --------------------------------
>
> Key: SINGA-176
> URL: https://issues.apache.org/jira/browse/SINGA-176
> Project: Singa
> Issue Type: New Feature
> Reporter: wangwei
> Assignee: Zheng Kaiping
>
> The loss base class 'Loss' is for learning objectives, which accept the
> prediction from the neural net and the target (or ground truth) from the
> training dataset. It outputs a scalar loss value for each data instance and
> computes the gradient of the loss value w.r.t the prediction value, which
> would be back-propagated through the neural net.
> The metric base class 'Metric' is for evaluating the performance (e.g,
> accuracy) of the neural net. It also accepts the prediction and the target,
> and computes the performance metrics, which could be accuracy, false
> positive, etc. It does not compute the gradients.
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