Write a Python program that takes as input the training dataset
posted on the class website (below this assignment) and outputs the
predicted labels of the corresponding test dataset. The datasets
are simulated GWAS under the logistic regression model. Most features
are noisy except for some that have signal. Use the nearest means 
classifier for this task. 

In the training dataset the top 1000 samples are cases and remainder
controls. In the test dataset the top 100 are cases and remainder are
controls. You must get at least 60% accuracy compared to the true 
labels. 

Submit your assignment by copying it into the directory
/afs/cad/courses/bnfo/f18/bnfo/615/001/<ucid>
For example if your ucid is abc12 then copy your solution into 
/afs/cad/courses/bnfo/f18/bnfo/615/001/abc12

Your completed assignment is due on December 10th 2018.