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))