GitHub - harpreet1237/salary_prediction_lasso_regression: This project compares the performance of two regression techniques Lasso and Ridge Regression and predicts salary of basket ball players.

harpreet1237 / salary_prediction_lasso_regression Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

This project compares the performance of two regression techniques Lasso and Ridge Regression and predicts salary of basket ball players.

0 stars 0 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
2020MCB1237_report.pdf		2020MCB1237_report.pdf
Hitters.csv		Hitters.csv
lasso.py		lasso.py
readme.txt		readme.txt

Repository files navigation

Assigned Project :
Do exploratory data analysis on the data. Use regression techniques
to predict the salary of baseball player. Use lasso technique also
and compare the results.

Steps to run the program: 
1. Please run the python file using appropriate command, python lasso.py 
2. At the end of the file, two functions are given : lassoRegression(X,y,testSize) and ridgeRegression(X,y,testSize) where arguments are X - multiple variables,
y - output (salaries), testSize = fraction of test sample needed. Both X,y are standardized data.
3. Code will run automatically these functions, you can edit the arguments if needed. 
4. Three figures will be produced by the code, i.e. alpha - ridge, alpha - lasso, heatmap of data.