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A-By using the perceptron rule learning, find the weights required to perform the following classification: vectors [1 -1 -1 1], [-1 -1 1 1] and [1 1 -1 1] are members of class with target value (-1); vector [ 1 1 1 -1] not a member of class with target value (1). Initially the weights and (e) are taken as zero Y= F(yin)= { 1 if yin > e 0 if yin ≤ e -1 if yin <-e B- By using Genetic algorithm, find the value of (y1, y2, y3, y4, y5) to the following equation. F(x)=(7*X1+ 2.4*X2 + 5.5 *X3 + 0.8 *X4 + 6.4*X5) F(x)=14 Error =1 f(x) new - f(x) /

A-By using the perceptron rule learning, find the weights required to perform the following classification: vectors [1 -1 -1 1], [-1 -1 1 1] and [1 1 -1 1] are members of class with target value (-1); vector [ 1 1 1 -1] not a member of class with target value (1). Initially the weights and (e) are taken as zero Y= F(yin)= { 1 if yin > e 0 if yin ≤ e -1 if yin <-e B- By using Genetic algorithm, find the value of (y1, y2, y3, y4, y5) to the following equation. F(x)=(7*X1+ 2.4*X2 + 5.5 *X3 + 0.8 *X4 + 6.4*X5) F(x)=14 Error =1 f(x) new - f(x) /

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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A-By using the perceptron rule learning, find the weights required to perform the following classification: vectors [1 -1 -1 1], [-1 -1 1 1] and [1 1 -1 1] are members of class with target value (-1); vector [ 1 1 1 -1] not a member of class with target value (1). Initially the weights and (e) are taken as zero Y= F(yin)= { 1 if yin > e 0 if yin ≤ e -1 if yin <-e B- By using Genetic algorithm, find the value of (y1, y2, y3, y4, y5) to the following equation. F(x)=(7*X1+ 2.4*X2 + 5.5 *X3 + 0.8 *X4 + 6.4*X5) F(x)=14 Error =1 f(x) new - f(x) /
Transcribed Image Text:A-By using the perceptron rule learning, find the weights required to perform the following classification: vectors [1 -1 -1 1], [-1 -1 1 1] and [1 1 -1 1] are members of class with target value (-1); vector [ 1 1 1 -1] not a member of class with target value (1). Initially the weights and (e) are taken as zero Y= F(yin)= { 1 if yin > e 0 if yin ≤ e -1 if yin <-e B- By using Genetic algorithm, find the value of (y1, y2, y3, y4, y5) to the following equation. F(x)=(7*X1+ 2.4*X2 + 5.5 *X3 + 0.8 *X4 + 6.4*X5) F(x)=14 Error =1 f(x) new - f(x) /
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