Prediction of Miles per gallon (MPG) Using Cars Dataset

In this we have coded in python to get the regression equation and find the confidence interval and prediction interval.

This file includes application of algorithms like logistic regression, Gaussian Naive Bayes and KNN and comparing their classification performances depending on whether the outliers have been dealt with or if interaction terms and higher degree features have been included.

Plotting of the Confidence interval and Prediction interval for a Linear Regression model.

Modeling daily electricity futures return variations from merit-order fundamentals using Huber and Ridge regression