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Given a dataset with 3 Boolean variables x1,x2 and a label/target Y, where Y = 1 a student has passed an exam. Figure below shows 4 samples , 3 positive (passed the exam), 1 negative (failed). X2 X1 a) If we train a KNN classifier (for K=1) on data above, which sample(s) will be misclassified by this KNN? +

Given a dataset with 3 Boolean variables x1,x2 and a label/target Y, where Y = 1 a student has passed an exam. Figure below shows 4 samples , 3 positive (passed the exam), 1 negative (failed). X2 X1 a) If we train a KNN classifier (for K=1) on data above, which sample(s) will be misclassified by this KNN? +

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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Given a dataset with 3 Boolean variables x1,x2 and a label/target Y, where Y = 1 a student has passed an exam. Figure below shows 4 samples ,3 positive (passed the exam), 1 negative (failed). X2 1 X1 a) If we train a KNN classifier (for K=1) on data above, which sample(s) will be misclassified by this KNN? (Hint: Remember what happens to KNN when K=1) b) Which classifier should be better for the data above and why? Logistic Regression or Linear Regression c) Could any Logistic Regression classifier perfectly classify data above? What will happen if we change the point (0,1) from 'plus +' to 'minus - +
Transcribed Image Text:Given a dataset with 3 Boolean variables x1,x2 and a label/target Y, where Y = 1 a student has passed an exam. Figure below shows 4 samples ,3 positive (passed the exam), 1 negative (failed). X2 1 X1 a) If we train a KNN classifier (for K=1) on data above, which sample(s) will be misclassified by this KNN? (Hint: Remember what happens to KNN when K=1) b) Which classifier should be better for the data above and why? Logistic Regression or Linear Regression c) Could any Logistic Regression classifier perfectly classify data above? What will happen if we change the point (0,1) from 'plus +' to 'minus - +
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