Exercise:Convolution and Pooling

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(Step 4: Test classifier)
(Step 4: Use pooled features for classification)
 
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=== Step 4: Use pooled features for classification ===
=== Step 4: Use pooled features for classification ===
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In this step, you will use the pooled features to train a softmax classifier to map the pooled features to the class labels. The code in this section uses <tt>softmaxTrain</tt> from the softmax exercise to train a softmax classifier on the pooled features for 500 iterations, which should take around 5 minutes.
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In this step, you will use the pooled features to train a softmax classifier to map the pooled features to the class labels. The code in this section uses <tt>softmaxTrain</tt> from the softmax exercise to train a softmax classifier on the pooled features for 500 iterations, which should take around a few minutes.
=== Step 5: Test classifier ===
=== Step 5: Test classifier ===
Now that you have a trained softmax classifier, you can see how well it performs on the test set. These pooled features for the test set will be run through the softmax classifier, and the accuracy of the predictions will be computed. You should expect to get an accuracy of around 80%.
Now that you have a trained softmax classifier, you can see how well it performs on the test set. These pooled features for the test set will be run through the softmax classifier, and the accuracy of the predictions will be computed. You should expect to get an accuracy of around 80%.

Latest revision as of 19:16, 3 June 2011

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