Using the Perceptron learning rule, Find the weights required to perform the following classifications: 1. Vectors...

 

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Using the Perceptron learning rule, Find the weights required to perform the following classifications: 1. Vectors (1,1,1,1) and (0,1,0,0) are members of the class, and therefore have target value 1. 2. Vectors (1,1,1,0) and (1,0,0,1) are not members of the class, and have target value 0. Use a learning rate of 1, 0p.3, and starting weights of 0. Using cach of the training vectors as input, test the responses of the net. Using the Perceptron learning rule, Find the weights required to perform the following classifications: 1. Vectors (1,1,1,1) and (0,1,0,0) are members of the class, and therefore have target value 1. 2. Vectors (1,1,1,0) and (1,0,0,1) are not members of the class, and have target value 0. Use a learning rate of 1, 0p.3, and starting weights of 0. Using cach of the training vectors as input, test the responses of the net.

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The perceptron learning rule obligates to study the ideal weight coefficient The above has the follo... View the full answer