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di = {X:(0, 1), p(Y = 0[X) = 0.3} dz = {X:(1, 0), p(Y = 0|X) = 0.7} dz = {X:(0, 0), p(Y = 0|X) = 0.5} %3D Find the decision boundary for this classifier. What is the prediction for the given test data di = {X:(-1, 0)}

di = {X:(0, 1), p(Y = 0[X) = 0.3} dz = {X:(1, 0), p(Y = 0|X) = 0.7} dz = {X:(0, 0), p(Y = 0|X) = 0.5} %3D Find the decision boundary for this classifier. What is the prediction for the given test data di = {X:(-1, 0)}

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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We want to train a binary Logistic Regression classifier for the given training
dataset:

di {X:(0, 1), p(Y = 0|X) = 0.3} d2 = {X:(1, 0), p(Y = 0|X) = 0.7} dz = {X:(0, 0), p(Y = 0|X) = 0.5} Find the decision boundary for this classifier. What is the prediction for the given test data: di {X:(-1, 0)}
Transcribed Image Text:di {X:(0, 1), p(Y = 0|X) = 0.3} d2 = {X:(1, 0), p(Y = 0|X) = 0.7} dz = {X:(0, 0), p(Y = 0|X) = 0.5} Find the decision boundary for this classifier. What is the prediction for the given test data: di {X:(-1, 0)}
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