- Matlab function banditE.m that implements the n-armed bandit problem using epsilon-greedy algorithm.
- Script to run banditE.m
- Matlab function banditS.m that implements the softmax strategy
- Script to run banditS.m
- Matlab function banditP.m that implements the pursuit strategy
- Script to run banditP.m

- Fourier Example 1: A known data set
- Fourier Example 2: Sunspots
- The Star Data
- The Letter E data
- Run the Letter E example

- Labels for Data below (labels.m) When you run labels.m, you will create a cell structure with names (this is actually a short script file). The names will be stored in "G".
- Taxonomy Data ( tax001.dat ) This is just a text array of data. Use the load command (like you did for the iris data).
- Plot routine: plotcell.m

Useage: once the network "net" is trained using data set X, and assuming you have run labels.m (above), then:

plotcell(net,X,G)

PROJECT ONE: MUSHROOM CLASSIFICATION

- Mushroom data as a Matlab file. Both the inputs (matrix X) and the targets (vector Y) are included. Right click with your mouse, and select "Save Link As..."

PROJECT TWO: ALPHABET RECOGNITION

- Matlab file containing the alphabet (as a 35 x 26 matrix) Right click with your mouse, and select "Save Link As..."
- Function to map a 35-dimensional vector back to a 5 x 7 grid (to see what the letters look like!)

Machine Learning Repository Most of these problems will be classification problems- either unsupervised (by clustering) or supervised (via neural nets). Lots of data here! There are data sets that are probably not appropriate for the project- be sure to clear your idea with me!