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@ -52,6 +52,8 @@ class Perceptron:
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epoch_count = epoch_count + 1
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epoch_count = epoch_count + 1
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# if you want controle the epoch or just by erro
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# if you want controle the epoch or just by erro
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if erro == False:
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if erro == False:
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print('\nEpoch:\n',epoch_count)
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print('------------------------\n')
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#if epoch_count > self.epoch_number or not erro:
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#if epoch_count > self.epoch_number or not erro:
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break
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break
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@ -105,6 +107,7 @@ samples = [
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[2.4482, 0.9455, 11.2095],
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[2.4482, 0.9455, 11.2095],
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[2.0149, 0.6192, 10.9263],
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[2.0149, 0.6192, 10.9263],
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[0.2012, 0.2611, 5.4631]
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[0.2012, 0.2611, 5.4631]
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]
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]
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exit = [-1, -1, -1, 1, 1, -1, 1, -1, 1, 1, -1, 1, -1, -1, -1, -1, 1, 1, 1, 1, -1, 1, 1, 1, 1, -1, -1, 1, -1, 1]
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exit = [-1, -1, -1, 1, 1, -1, 1, -1, 1, 1, -1, 1, -1, -1, -1, -1, 1, 1, 1, 1, -1, 1, 1, 1, 1, -1, -1, 1, -1, 1]
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@ -114,12 +117,7 @@ network = Perceptron(sample=samples, exit = exit, learn_rate=0.01, epoch_number=
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network.trannig()
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network.trannig()
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while True:
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while True:
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i = 0
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sample = []
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sample = []
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while i < 3:
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for i in range(3):
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value = input('value: ')
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sample.insert(i, float(input('value: ')))
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value = float(value)
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sample.insert(i, value)
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i = i + 1
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network.sort(sample)
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network.sort(sample)
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