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Deep Learning: Difference between revisions
→Loss functions
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For multi-way classification, can use cross-entropy loss: | For multi-way classification, can use cross-entropy loss: | ||
<math>g(z)=\frac{1}{1+e^{-z}}</math> | <math>g(z)=\frac{1}{1+e^{-z}}</math> | ||
<math>-\sum_{i=1}^{N}\left[y_i\log(y(f_W(x)) + (1-y_i)\log(1-g(f_W(x))\right]</math> | <math>\min_{W} -\sum_{i=1}^{N}\left[y_i\log(y(f_W(x)) + (1-y_i)\log(1-g(f_W(x))\right]</math> | ||
==Misc== | ==Misc== | ||