Description

To learn how to use the BP algorithm to train a multi-layer network. The provided code should be written by Python, Matlab, or C/C++.

Requirement

By using the BP algorithm. This time, however, students need to design a three layers network (i.e., three hidden layers) and carefully train the network with one classification dataset selected from the UCI dataset library. (https://archive.ics.uci.edu/ml/datasets.php). Provide your testing accuracy on the selected dataset.

Select a regression dataset from the UCI dataset library. Then using BP to train a three layers network and provide your testing/training root mean square error.

Please select the SGDM optimizer in the training process.

To learn how to use the BP algorithm to train a multi-layer network. The provided code should be written by Python, Matlab, or C/C++. equirement - (6 marks) Repeat the computer experiment mentioned in the class by using the BP algorithm. This time, however, students need to design a three layers network (i.e., three hidden layers) and carefully train the network with one classification dataset selected from the UCI dataset library. (https://archive.ics.uci.edu/ml/datasets.php). Provide your testing accuracy on the selected dataset. - (2 marks) Select a regression dataset from the UCI dataset library. Then using BP to train a three layers network and provide your testing/training root mean square error. - (2 marks) Please select the SGDM optimizer in the training process