Changing the feature vector

All code has been organized so that the same code can handle generation of all datasets and running all the learning experiments. The following changes have been made to the feature generation code:

1. Removing the translation in variance factor.
2. Removing the scale invariance factor.
3. Decreasing the number of bins in CDF attributes 0 - 5, 6 - 10 to 0 - 10, 11 - 20 etc.
4. Removing the histogram attributes.

The code to generate all datasets is in the files generateFeatures.m and momentCalc9.m in the following location /usr/sci/crcnsdata/CRCNS/Synapses/Code/Matlab/featureGeneration. The generateFeatures function takes the dataset name as argument and generates the datasets. The run.m has been modified so that it takes the dataset and learner types are inputs and learns accordingly.

After this change was done the new datasets were generated for the following datasets:

1. Synapses Dataset
2. Tough Brodatz Textures Dataset
   
3. Cell Membrane Dataset

Once the datasets have been generated. Both the perceptron classifier and decision stump classifiers were used to learn over them.

The results of the various experiments are shown in the below graphs. Left side graphs are Stump based classifiers and perceptron classifier results to the right.

Tough Brodatz Textures Dataset Results: This experiment was run with a required true positive rate of 0.7


Synapses Dataset Results: This experiment was run with a required true positive rate of 0.7


Cell Membrane Dataset Results: This experiment was run with a required true positive rate of 0.7