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2015/03/08 21:02 kubalik
2015/03/08 21:00 kubalik
2013/10/04 13:02 external edit
2011/03/02 16:31 kubalik
2011/03/02 16:30 kubalik created
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2015/03/08 21:02 kubalik
2015/03/08 21:00 kubalik
2013/10/04 13:02 external edit
2011/03/02 16:31 kubalik
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courses:ae4m33bia:guidelines_ann [2013/10/04 13:02]
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courses:ae4m33bia:guidelines_ann [2015/03/08 21:02]
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**Guidelines for ANN Assignment**
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- Choose an appropriate dataset.
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- Search for an optimal ANN architecture (a number of hidden layers and their neurons).
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- Experimentally find appropriate number of epochs.
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- Experiment with:
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* Backpropagation,
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* Batch Backpropagation,
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* Backpropagation with momentum,
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* Quickpropagation,
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* Resilient propagation (RPRop).
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- For backpropagation test at least 3 settings of a learning rate/step width and 3 settings of momentum constant for a version of BP with Momentum.
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- Focus on a learning speed and ANN total error.
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- Write a report documenting all your experiments. It should include:
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* Description of the dataset - number and types of attributes, number of instances. For classification task also the number of classes and the class distribution.
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* Description of a chosen ANN topology and the process of finding the optimal topology.
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* Description of experiments.
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* Typical learning behavior plots for chosen learning algorithms and parameter settings including the discussion.
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* Analysis of experiments and a Conclusion.
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- Your work does not have to exactly match the above guidelines. These should rather give you an overview of the amount of work required.
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courses/ae4m33bia/guidelines_ann.1380884573.txt.gz
· Last modified: 2015/03/08 21:00 (external edit)