Multi-class Classification and Neural Networks

Introduction

• Implement one-vs-all logistic regression and neural networks to recognize hand-written digits.

Files included in this exercise

• ex3.m - Octave/MATLAB script that steps you through part 1
• ex3 nn.m - Octave/MATLAB script that steps you through part 2
• ex3data1.mat - Training set of hand-written digits
• ex3weights.mat - Initial weights for the neural network exercise
• submit.m - Submission script that sends your solutions to our servers
• displayData.m - Function to help visualize the dataset
• fmincg.m - Function minimization routine (similar to fminunc)
• sigmoid.m - Sigmoid function
• [?] lrCostFunction.m - Logistic regression cost function
• [?] oneVsAll.m - Train a one-vs-all multi-class classifier
• [?] predictOneVsAll.m - Predict using a one-vs-all multi-class classifier
• [?] predict.m - Neural network prediction function
• ? indicates files you will need to complete

IDE : Octave_4.4.0

ex3.zip