ML Project 2
For the latest project, my Machine Learning professor gave us some sample code (in C) and we have to:
- Convert the sample into the language we’ll be using (Python in my case) and compile & run the linear regression model on the training data, calculating the error using a function.
- Modify the program to accept both the training data and the test data files and run it, calcuating the error for both.
- Rewrite the linear model for regression to work as a classifier, and run it on another set of test and training files, calculating the accuracy.
- Modify the code to use a regularization technique and run the classification model on reduced training and testing data sets with a series of regularization coefficients, calculating the accuracy.
- Write a report comparing and explaining the results.
This is a big challenge, but the first step is for me to convert some C functions he gave us to Python functions (we’re not allowed to use any built-in functions), so I’m off to get started!
Oh yeah, and the dataset has 8 inputs and 7 outputs. 1768 rows.
Hi Renee,
Thanks a lot for providing very useful model and examples.
Also i would like to understand excel model through skype. Please let me know good time to discuss as i am beginner in Statistics.
I’m sorry, I don’t have time to provide guidance over Skype to people on an individual basis. If you want a private tutor, check out sites like Springboard. If you are looking for beginner stats help, I suggest Khan Academy videos. If you’re looking for data science in Excel, I’ll suggest John Foreman’s book Data Smart. Good luck with your learning! Please post if you have general questions that can help others, or if you find resources that were particularly useful to you.