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Posted to dev@singa.apache.org by "wangwei (JIRA)" <ji...@apache.org> on 2016/05/20 11:58:12 UTC

[jira] [Created] (SINGA-176) Add loss and metric base classes

wangwei created SINGA-176:
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             Summary: 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


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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