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Study mode:
on
1
Intro
2
Key points from previous lecture
3
Automotive Crash Testing- Problem Statement
4
Getting things ready
5
Reading the data
6
Understanding the data
7
Structure of the data
8
Structure of train data
9
Building a logistic regression model
10
Summary of model
11
Finding the odds predict()
12
Plotting the probabilities
13
Identifying probabilities associated with the Car Type
14
Predicting on test data
15
Confusion matrix
Description:
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

NPTEL-NOC IITM
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