[SOLVED] Cs725 homework 1- logistic regression and linear classification

Setting up
Instructions
For logistic regression: python train.py –dataset binary –model logistic_regression –num_epochs <num_epochs> -learning_rate <learning_rate> –momentum <momentum>
For linear classifier: python train.py –dataset iris –model linear_classifier –num_epochs <num_epochs> -learning_rate <learning_rate> –momentum <momentum>
The default values for each of these parameters are available in args.py
Submission
Once you are done with both the tasks, copy weights corresponding to your best models for each dataset into submission/ directory. Also copy the completed version (implementing both models) of model.py and your observation report (with filename report.pdf) into the same directory. Overall, make sure your submission folder looks as below. This is crucial since the assignment will be autograded: submission/ model.py best_binary.weights.npy best_iris.weights.npy report.pdf You can get a hint of the accuracy and loss values that autograder will use for grading your submission by running python evaluate_submission.py in this directory itself. The observation report should also contain roll numbers of both students in the team.
Once you are satisfied with the submission, use tar -cvzf <roll1>_<roll2>.tar.gz submission/ to create the final submission. Only the student with lower roll number in the group needs to upload this .tar.gz on Moodle.
Visualizing (Optional)