symmetrical-adventure

This was our final assignment for Semester 1 Machine Learning.

We were told to Use the usps data set from https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/ and report precision and recall for each class in the data set.

USPS_DATASET/TrainUSPS = Training File USPS_DATASET/Test = testing file. Also contains outputs for creating ground truth file to check accuracy of classifier.

##Steps Followed:

1. Download libsvm
2. Read README of libsvm
3. Go to downloaded folder of libsvm via terminal
4. Execute the make commmand for your system.
5. Download USPS dataset
6. Copy Datasets to libsvm folder.
7. Run following Commands 8 and 9 in terminal.
8. ./svm-train USPS_DATASET/TrainUSPS
9. ./svm-predict USPS_DATASET/Test TrainUSPS.model USPS_DATASET/OutputValue

• Step 8. trains the svm and creates a model file.
• Step 9. Makes prediction on test file using Model and outputs the predictions into a file and prints the accuracy of classification.

Now that predictions have been made, I made a simple calculator for finding the precision and recall for each class in the dataset.It can be found under USPS_DATASET/precision.py. 10. Run the command: python precision.py GroundTruth OutputValue. This calculates the Recall and precision for all classes.

##Appendix

• USPS_DATASET/TrainUSPS = Training File
• USPS_DATASET/Test = testing file. Also contains outputs for creating ground truth file to check accuracy of classifier.
• TrainUSPS.model = Model file created after running Step 8.
• OutputValue = File where we saved all predictions.
• GroundTruth = Only Class/Labels from the test file.

###Created for Dr. Asharaf S.