Created
December 20, 2018 02:34
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Implementation of OR gate using perceptron
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| import numpy as np | |
| input1 = [0,0,1,1] | |
| input2 = [1,0,1,0] | |
| truth = [0,1,0,1] | |
| weight1 = 0 | |
| weight2 = -1 | |
| bias = 0 | |
| def perceptron(input1, input2): | |
| score = (input1* weight1) + (input2 * weight2) + bias | |
| if score >= 0: | |
| return 1 | |
| else: | |
| return 0 | |
| def test_perceptron(): | |
| assert perceptron(input1[0],input2[0]) == truth[0] | |
| assert perceptron(input1[1],input2[1]) == truth[1] | |
| assert perceptron(input1[2],input2[2]) == truth[2] | |
| assert perceptron(input1[3],input2[3]) == truth[3] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import numpy as np | |
| input1 = [0,0,1,1] | |
| input2 = [1,0,1,0] | |
| truth = [1,0,1,1] | |
| weight1 = 1 | |
| weight2 = 1 | |
| bias = -1 | |
| def perceptron(input1, input2): | |
| score = (input1* weight1) + (input2 * weight2) + bias | |
| if score >= 0: | |
| return 1 | |
| else: | |
| return 0 | |
| def test_perceptron(): | |
| assert perceptron(input1[0],input2[0]) == truth[0] | |
| assert perceptron(input1[1],input2[1]) == truth[1] | |
| assert perceptron(input1[2],input2[2]) == truth[2] | |
| assert perceptron(input1[3],input2[3]) == truth[3] |
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