def p_xor():
X = np.array([(0,0),(0,1),(1,0),(1,1)])
y = np.array([[0],[1],[1],[0]])
print("[INFO] training perceptron...")
p = perceptron.Perceptron(X.shape[1],alpha=0.1)
p.fit(X,y,epochs=20)
print("[INFO] testing perceptron...")
for(x,target) in zip(X,y):
pred = p.predict(x)
print("[INFO] data={},group-truth={},pred={}".format(x,target[0],pred))
from pyimagesearch.nn import perceptron
import numpy as np
X = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y = np.array([[0], [1], [1], [1]])
print("[INFO] training perceptron...")
p = perceptron.Perceptron(X.shape[1], alpha=0.1)
p.fit(X, y, epochs=20)
print("[INFO] testing perceptron...")
for (x, target) in zip(X, y):
pred = p.predict(x)
print("[INFO] data={}, ground-truth={}, pred={}".format(
x, target[0], pred))