To understand Polynomial Fitting, I've created a basic model from scratch.
Problem : Given a data set of web status which contains number of requests per hour. Task is to find when the number of web hits would reach 1,00,000.
- Reading and visualizing the data - done in the ch1.py file
- creating the error function - in ErrorFn.py file
- finding the best polynomial function - in segregatingData.py file
- Testing the model using the web_test dataset.
- Calculating when the web-hits would reach 1,00,000 per hour - result.py