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Implementation, Part1

import numpy as np

from collections import Counter

class Perceptron:

def __init__(self, input_length, weights=None):

if weights==None:

self.weights = np.random.random((input_length))*2 - 1

self.learning_rate = 0.1

@staticmethod

def unit_step_function(x):

if x < 0:

return 0

return 1

def __call__(self, in_data):

weighted_input = self.weights * in_data

weighted_sum = weighted_input.sum()

return Perceptron.unit_step_function(weighted_sum)