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UML501 Lab 5 Solution

Machine Learning (UML501)
Multiclass Logistic Regression Implement Multiclass Logistic Regression (step-bystep) on Iris dataset using one vs. rest strategy?
Ridge Logistic Regression Download the exam dataset from the following link:
https ://drive.google.com/file/d/lwH60fvN GP mORFlCLt72W GhJYPZiXstY h/v iew

The dataset labels that whether or not the student Will get admission on the basis of the two exam scores. The plot of the data against examl and exam2

-0.75 -0.50 -0.25 000 025 0.50 0.75 1.00
Test 1
As clear from the figure, alinear decision boundary does not fit well. So, fit a Logistic Regression Classifier with polynomial function oftestl and test2 scores upto degree
6 using
1. Step-by-Step Logistic Regression (with no regularization; alpha—I O; number of iterations—1000) ii. Step-by-Step Logistic Regression (with ridge regularization; alpha—10; number of iterations—1000; lambda=0.2)

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