Explore logistic regression implementation in R through this 21-minute video lecture. Dive into automotive crash testing analysis, starting with data preparation and understanding. Learn to build a logistic regression model, interpret its summary, and calculate odds. Visualize probabilities, examine car type associations, and make predictions on test data. Conclude by constructing and interpreting a confusion matrix to evaluate model performance.
Logistic Regression Implementation in R for Automotive Crash Testing
Overview
Syllabus
Intro
Key points from previous lecture
Automotive Crash Testing- Problem Statement
Getting things ready
Reading the data
Understanding the data
Structure of the data
Structure of train data
Building a logistic regression model
Summary of model
Finding the odds predict()
Plotting the probabilities
Identifying probabilities associated with the Car Type
Predicting on test data
Confusion matrix
Taught by
NPTEL-NOC IITM
