Assignment 7
Machine Learning: Regression and Classification
Due Date: Wednesday, May 18th, 11:59:59 PM
Value: 150 points
Github Invite: Click Here
Collaboration: For Assignment 7, collaboration is not allowed; you must work individually. You may still come to office hours for help, but you may not work with any other CMSC 210 students. You may post questions on Discord, but you may not post code.
Objectives:
- Bivariate, Multivariate, and Polynomial Linear regression
- Classification with Naive Bayes and Decision Trees
Instructions
This assignment is to be done in Jupyter lab notebooks. Instructions for setting this up are in the README of the assignment Github repo.
The assignment consists of two parts, each contained in a notebook file. Part one involves linear regression and is contained in gas-mileage.ipynb.
Part two involves classification and is contained in seed-classification.ipynb.
To complete the assignment, start up the Jupyter Lab server, update the two notebooks listed above with your work, save them, commit the results, and push to GitHub.
Grading Rubric
| Bivariate Linear Regression: MSE calculated | 15 points |
| Bivariate Linear Regression: data plotted | 15 points |
| Polynomial Regression: MSE calculated | 15 points |
| Polynomial Regression: data plotted | 15 points |
| Multivariate Linear Regression: MSE calculated | 15 points |
| Multivariate Linear Regression: predictions made | 15 points |
| Classification: Naive Bayes Model Trained | 15 points |
| Classification: Decision Tree Model Trained | 15 points |
| Classification: Naive Bayes Accuracy Calculated | 15 points |
| Classification: Decision Tree Accuracy Calculated | 15 points |
| Total: | 150 points |