Homework SourseCould a singlelayer perceptron with input xx1x2xn and output
Could a single-layer perceptron with input x=(x1,x2,...,xn) and output y=[w.x-b]+ learn to classify the following training data? If yes, provide a weight vector and bias b. If not, explain why not.
The positive data (the expected lable is 1) is {(1,1),(1.5,2),(0.1,1.3),(2,1)} and the negative data is {(2.5,1),(3,5),(1.5,3)}
Solution
A LEARNING ALGORTHM IS ANADAPTIVE METHODBY WHICH A NETWORKOFCOMPUTING UNITS SELF ORGANIZES TOIMPLEMENTTHE DESIRED BEHAVIIOUR THIS IS DONE INSOME LEARNING ALGORITHMSBY PRESENTING THE DESIRED BEHAVIOUR THIS CONCEPT IS WORK IN THIS QUESTION THAT IS WHY WE GOT SUCH ANS
![Could a single-layer perceptron with input x=(x1,x2,...,xn) and output y=[w.x-b]+ learn to classify the following training data? If yes, provide a weight vector](/WebImages/28/could-a-singlelayer-perceptron-with-input-xx1x2xn-and-output-1074974-1761563654-0.webp "Could a single-layer perceptron with input x=(x1,x2,...,xn) and output y=[w.x-b]+ learn to classify the following training data? If yes, provide a weight vector")
