Week 8 (July 15 –July 21) Progress

Started work on backpropagation for ClassificationNeuralNetwork class

After reviewing the MATLAB documentation, I successfully implemented the following components for the ClassificationNeuralNetwork class:

  1. Weights Initializer: Layer weights are initialized using either 'glorot' or 'he'. (Helper function)
  2. Biases Initializer: Biases are initialized using either 'zeros' or 'ones'. (Helper function)
  3. Loss Function: Cross entropy. (Helper function)
  4. One-Hot Vector Encoder: (Helper function)

I ran various tests to ensure everything is working correctly, such as:

  1. Cross Entropy Loss Function: I created matrices for y_pred and y_act and fed them to an online function and to my implementation. The outputs matched.
  2. Forward Propagation: I used trained weights and biases from MATLAB for the Fisheriris dataset, gave them to my predict function, and the outputs were the same.

The only remaining task is backpropagation, and I am facing some issues like non-conformant arguments (matrix multiplication problems). I will try to resolve this before our meeting. You can see my work here. Any help related to the algorithm part is greatly appreciated.

Resources I found helpful include:

Our next meeting is scheduled for July 23rd at 16:30 UTC. Also, the Olympics are going to start on the 26th, so I will try to complete all my work before then. See you in the next blog. 😄

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