Exercise: Implement deep networks for digit classification

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(Step 4: Implement fine-tuning)
(Step 5: Test the model: Changed accuracy figures)
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Finally, you will need to classify with this model; complete the code in <tt>stackedAEPredict.m</tt> to classify using the stacked autoencoder with a classification layer.
Finally, you will need to classify with this model; complete the code in <tt>stackedAEPredict.m</tt> to classify using the stacked autoencoder with a classification layer.
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After completing these steps, running the entire script in stackedAETrain.m will perform layer-wise training of the stacked autoencoder, finetune the model, and measure its performance on the test set. If you've done all the steps correctly, you should get an accuracy of about 97.6% (for the 10-way classification problem).
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After completing these steps, running the entire script in stackedAETrain.m will perform layer-wise training of the stacked autoencoder, finetune the model, and measure its performance on the test set. If you've done all the steps correctly, you should get an accuracy of about 87.7% before finetuning and 97.6% after finetuning (for the 10-way classification problem).

Revision as of 06:55, 20 May 2011

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