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From GitBox <...@apache.org>
Subject [GitHub] hwjwayne opened a new issue #8933: How to train data with multi-class label
Date Thu, 01 Jan 1970 00:00:00 GMT
hwjwayne opened a new issue #8933: How to train data with multi-class label
URL: https://github.com/apache/incubator-mxnet/issues/8933
 
 
   There are 600 classes in the image dataset, each image belongs to one or more classes.
How can I train such dataset?
   
   **Is it a correct choice:**
   Present image label by 600*1 binary vector, which contains one or more "1".
   Bulid network with 600 outputs, and activate them with LogisticRegressionOutput()  (BTW,
Will mxnet set the loss function to logistic loss automatically?)
   
   I obtain a 0.49% mAP on this dataset, by it's reported 36.1% in the paper. (Parameters
are set the same as the paper)

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