120 lines
2.5 KiB
Python
120 lines
2.5 KiB
Python
# 26696.5 26399.0 27074.0
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# [1204.8199999999993, 3279.9473790382926, -17453.52050319462, 20734.836596930876, -19276.958435444365, -11703.66716416129, -29009.135804905836, 17108.712660770405, -11751.94058615113, -4730.670939823587, 15953.080371721595, -6169.31607964013, -10440.140127478617]
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import random
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from datetime import datetime
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import matplotlib.pyplot as plt
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class PLA():
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def __init__(self, data):
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self.data = data
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self.dim = len(self.data[0]['x'])
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self.w = [0] * self.dim
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def iterate(self):
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'''
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randomly picks an example (x_n, y_n) in every iteration.
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updates wt if and only if w_t is incorrect on the example.
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Inputs:
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None
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Outputs:
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mistake: bool.
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'''
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index = random.randint(0, len(data)-1)
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mistake = 1 if sign(dot(self.w, self.data[index]['x'])) != self.data[index]['y'] else 0
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if mistake:
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self.update(index)
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return mistake
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def update(self, index):
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'''
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w_(t+1) = w_t + y_t*x_t
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Inputs:
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index: which row need to use for updating weight
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Outputs:
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None
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'''
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for i in range(self.dim):
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self.w[i] = self.w[i] + self.data[index]['y'] * self.data[index]['x'][i]
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def read_file():
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'''
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read numbers from 'hw1_train.dat'
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Inputs:
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None
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Outputs:
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data: dict list. each dict has ('x', 'y') pair
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x is a list contains 12 numbers.
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y is either 1 or -1.
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'''
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with open('hw1_train.dat') as fp:
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data = []
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lines = fp.readlines()[:-1]
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for line in lines:
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numbers = line.split()
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x = [ float(i)*11.26 for i in numbers[:-1] ]
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x.insert(0,11.26)
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y = int(numbers[-1])
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data.append({
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'x': x,
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'y': y,
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})
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return data
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def dot(a, b):
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'''
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dot product
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Inputs:
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a: a list
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b: a list. its length must be equal to len(a)
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Outputs:
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ans: a number
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'''
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ans = 0
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assert len(a)==len(b)
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for i in range(len(a)):
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ans += a[i] * b[i]
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return ans
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def sign(a):
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'''
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positive || negative
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Inputs:
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a: a number
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Outputs:
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ans: 1 or -1, means this is positive or negative
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'''
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return 1 if a>0 else -1
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if __name__ == '__main__':
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data = read_file()
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log = []
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for i in range(1000):
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random.seed(datetime.now().timestamp())
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pla = PLA(data)
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counter = 0
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stopping_counter = 0
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while 1:
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mistake = pla.iterate()
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counter += 1
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if mistake:
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stopping_counter = 0
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else:
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stopping_counter += 1
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if stopping_counter == (5*len(data)):
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break
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log.append(counter)
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sorted_log = sorted(log)
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print("medium: {}".format((sorted_log[499]+sorted_log[500])/2))
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plt.hist(log, bins=100)
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plt.savefig('./hw1_10.png')
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plt.show()
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print(pla.w) |