我正在实现 AND 感知器,但在决定组合的权重和偏差以将其与 AND 真值表相匹配时面临困难。
这是我编写的代码:
import pandas as pd
# Set weight1, weight2, and bias
weight1 = 2.0
weight2 = -1.0
bias = -1.0
# Inputs and outputs
test_inputs = [(0, 0), (0, 1), (1, 0), (1, 1)]
correct_outputs = [False, False, False, True]
outputs = []
# Generate and check output
for test_input, correct_output in zip(test_inputs, correct_outputs):
linear_combination = weight1 * test_input[0] + weight2 * test_input[1] + bias
output = int(linear_combination >= 0)
is_correct_string = 'Yes' if output == correct_output else 'No'
outputs.append([test_input[0], test_input[1], linear_combination, output, is_correct_string])
# Print output
num_wrong = len([output[4] for output in outputs if output[4] == 'No'])
output_frame = pd.DataFrame(outputs, columns=['Input 1', ' Input 2', ' Linear Combination', ' Activation Output', ' Is Correct'])
if not num_wrong:
print('Nice! You got it all correct.\n')
else:
print('You got {} wrong. Keep trying!\n'.format(num_wrong))
print(output_frame.to_string(index=False))
我必须根据提到的值来决定权重1、权重2和偏差。当输入为 1
和 0
时,我得到一个输出错误。
感谢您的帮助。
最佳答案
- 该方程是对称的:两个输入在功能上是等效的。
- 将权重作为变量,三个(现在是两个)变量中有四个(现在是三个)不等式。您在解决该系统问题上陷入了哪些困境?
系统:
w = weight (same for both inputs)
b = bias
0*w + 0*w + b <= 0
1*w + 0*w + b <= 0
1*w + 1*w + b > 0
这给你留下了
w + b <= 0
2*w + b > 0
您应该能够从那里描述可能的解决方案。
关于python - AND 感知器的权重和偏差是多少?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53822167/