def perceptronTrainTest(X, y):
# training the perceptron. N is the number of data points
print("[INFO] training perceptron...")
p = Perceptron(X.shape[1], alpha=0.1)
p.fit(X, y, epochs=20)
# evaluating
print("[INFO] testing perceptron...")
for (x, target) in zip(X, y):
print(f'Input: {x}, expected: {target}, predicted: {p.predict(x)}')
from pyimagesearch.nn.perceptron 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(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))