commit aed176de2a88c4432b8adc25b4fcaaa4912d25cb Author: snsd0805 Date: Sun Sep 17 23:48:22 2023 +0800 feat: HW1 version 1. complete hw1 9~12 diff --git a/hw1_10.py b/hw1_10.py new file mode 100644 index 0000000..ab5d45c --- /dev/null +++ b/hw1_10.py @@ -0,0 +1,120 @@ +# 26696.5 26399.0 27074.0 +# [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] + +import random +from datetime import datetime +import matplotlib.pyplot as plt + +class PLA(): + def __init__(self, data): + self.data = data + self.dim = len(self.data[0]['x']) + self.w = [0] * self.dim + + def iterate(self): + ''' + randomly picks an example (x_n, y_n) in every iteration. + updates wt if and only if w_t is incorrect on the example. + + Inputs: + None + Outputs: + mistake: bool. + ''' + index = random.randint(0, len(data)-1) + mistake = 1 if sign(dot(self.w, self.data[index]['x'])) != self.data[index]['y'] else 0 + if mistake: + self.update(index) + return mistake + + def update(self, index): + ''' + w_(t+1) = w_t + y_t*x_t + + Inputs: + index: which row need to use for updating weight + Outputs: + None + ''' + for i in range(self.dim): + self.w[i] = self.w[i] + self.data[index]['y'] * self.data[index]['x'][i] + +def read_file(): + ''' + read numbers from 'hw1_train.dat' + + Inputs: + None + Outputs: + data: dict list. each dict has ('x', 'y') pair + x is a list contains 12 numbers. + y is either 1 or -1. + ''' + with open('hw1_train.dat') as fp: + data = [] + lines = fp.readlines()[:-1] + for line in lines: + numbers = line.split() + x = [ float(i)*11.26 for i in numbers[:-1] ] + x.insert(0,11.26) + y = int(numbers[-1]) + + data.append({ + 'x': x, + 'y': y, + }) + return data + +def dot(a, b): + ''' + dot product + + Inputs: + a: a list + b: a list. its length must be equal to len(a) + Outputs: + ans: a number + ''' + ans = 0 + assert len(a)==len(b) + for i in range(len(a)): + ans += a[i] * b[i] + return ans + +def sign(a): + ''' + positive || negative + + Inputs: + a: a number + Outputs: + ans: 1 or -1, means this is positive or negative + ''' + return 1 if a>0 else -1 + +if __name__ == '__main__': + data = read_file() + log = [] + for i in range(1000): + random.seed(datetime.now().timestamp()) + pla = PLA(data) + + counter = 0 + stopping_counter = 0 + while 1: + mistake = pla.iterate() + counter += 1 + if mistake: + stopping_counter = 0 + else: + stopping_counter += 1 + if stopping_counter == (5*len(data)): + break + log.append(counter) + + sorted_log = sorted(log) + print("medium: {}".format((sorted_log[499]+sorted_log[500])/2)) + plt.hist(log, bins=100) + plt.savefig('./hw1_10.png') + plt.show() + print(pla.w) \ No newline at end of file diff --git a/hw1_11.py b/hw1_11.py new file mode 100644 index 0000000..e2d5fc3 --- /dev/null +++ b/hw1_11.py @@ -0,0 +1,120 @@ +# 25428.0 25891.5 26446.5 +# [1002.1399999999994, 223.21665372403237, -1291.848080071952, 1515.5600276924624, -1404.8070879687737, -887.5562485642265, -2129.790874533273, 1268.8912058979067, -893.1255882425288, -358.771941045434, 1161.2662431910446, -499.8519798398823, -806.2229919825804] + +import random +from datetime import datetime +import matplotlib.pyplot as plt + +class PLA(): + def __init__(self, data): + self.data = data + self.dim = len(self.data[0]['x']) + self.w = [0] * self.dim + + def iterate(self): + ''' + randomly picks an example (x_n, y_n) in every iteration. + updates wt if and only if w_t is incorrect on the example. + + Inputs: + None + Outputs: + mistake: bool. + ''' + index = random.randint(0, len(data)-1) + mistake = 1 if sign(dot(self.w, self.data[index]['x'])) != self.data[index]['y'] else 0 + if mistake: + self.update(index) + return mistake + + def update(self, index): + ''' + w_(t+1) = w_t + y_t*x_t + + Inputs: + index: which row need to use for updating weight + Outputs: + None + ''' + for i in range(self.dim): + self.w[i] = self.w[i] + self.data[index]['y'] * self.data[index]['x'][i] + +def read_file(): + ''' + read numbers from 'hw1_train.dat' + + Inputs: + None + Outputs: + data: dict list. each dict has ('x', 'y') pair + x is a list contains 12 numbers. + y is either 1 or -1. + ''' + with open('hw1_train.dat') as fp: + data = [] + lines = fp.readlines()[:-1] + for line in lines: + numbers = line.split() + x = [ float(i) for i in numbers[:-1] ] + x.insert(0,11.26) + y = int(numbers[-1]) + + data.append({ + 'x': x, + 'y': y, + }) + return data + +def dot(a, b): + ''' + dot product + + Inputs: + a: a list + b: a list. its length must be equal to len(a) + Outputs: + ans: a number + ''' + ans = 0 + assert len(a)==len(b) + for i in range(len(a)): + ans += a[i] * b[i] + return ans + +def sign(a): + ''' + positive || negative + + Inputs: + a: a number + Outputs: + ans: 1 or -1, means this is positive or negative + ''' + return 1 if a>0 else -1 + +if __name__ == '__main__': + data = read_file() + log = [] + for i in range(1000): + random.seed(datetime.now().timestamp()) + pla = PLA(data) + + counter = 0 + stopping_counter = 0 + while 1: + mistake = pla.iterate() + counter += 1 + if mistake: + stopping_counter = 0 + else: + stopping_counter += 1 + if stopping_counter == (5*len(data)): + break + log.append(counter) + + sorted_log = sorted(log) + print("medium: {}".format((sorted_log[499]+sorted_log[500])/2)) + plt.hist(log, bins=100) + plt.savefig('./hw1_11.png') + plt.show() + print(pla.w) \ No newline at end of file diff --git a/hw1_12.py b/hw1_12.py new file mode 100644 index 0000000..cf5814c --- /dev/null +++ b/hw1_12.py @@ -0,0 +1,125 @@ +# 26184.0, 26893.0 +# [93, 271.62041274205694, -1299.0824702542302, 1581.364721945991, -1414.3324363288546, -921.8008924538738, -2246.111150883575, 1307.67736423112, -900.7139136505582, -357.75401412080953, 1239.9915965507037, -514.1026403861741, -799.7272198274563] + +import random +from datetime import datetime +import matplotlib.pyplot as plt + +class PLA(): + def __init__(self, data): + self.data = data + self.dim = len(self.data[0]['x']) + self.w = [0] * self.dim + self.choose = random.randint(0, len(self.data)-1) + + def iterate(self): + ''' + randomly picks an example (x_n, y_n) in every iteration. + updates wt if and only if w_t is incorrect on the example. + + Inputs: + None + Outputs: + mistake: bool. + ''' + # index = random.randint(0, len(data)-1) + mistake = 1 if sign(dot(self.w, self.data[self.choose]['x'])) != self.data[self.choose]['y'] else 0 + if mistake == 0: + self.choose = random.randint(0, len(data)-1) + mistake = 1 if sign(dot(self.w, self.data[self.choose]['x'])) != self.data[self.choose]['y'] else 0 + # print(self.choose) + if mistake: + self.update(self.choose) + return mistake + + def update(self, index): + ''' + w_(t+1) = w_t + y_t*x_t + + Inputs: + index: which row need to use for updating weight + Outputs: + None + ''' + for i in range(self.dim): + self.w[i] = self.w[i] + self.data[index]['y'] * self.data[index]['x'][i] + +def read_file(): + ''' + read numbers from 'hw1_train.dat' + + Inputs: + None + Outputs: + data: dict list. each dict has ('x', 'y') pair + x is a list contains 12 numbers. + y is either 1 or -1. + ''' + with open('hw1_train.dat') as fp: + data = [] + lines = fp.readlines()[:-1] + for line in lines: + numbers = line.split() + x = [ float(i) for i in numbers[:-1] ] + x.insert(0,1) + y = int(numbers[-1]) + + data.append({ + 'x': x, + 'y': y, + }) + return data + +def dot(a, b): + ''' + dot product + + Inputs: + a: a list + b: a list. its length must be equal to len(a) + Outputs: + ans: a number + ''' + ans = 0 + assert len(a)==len(b) + for i in range(len(a)): + ans += a[i] * b[i] + return ans + +def sign(a): + ''' + positive || negative + + Inputs: + a: a number + Outputs: + ans: 1 or -1, means this is positive or negative + ''' + return 1 if a>0 else -1 + +if __name__ == '__main__': + data = read_file() + log = [] + for i in range(1000): + random.seed(datetime.now().timestamp()) + pla = PLA(data) + + counter = 0 + stopping_counter = 0 + while 1: + mistake = pla.iterate() + counter += 1 + if mistake: + stopping_counter = 0 + else: + stopping_counter += 1 + if stopping_counter == (5*len(data)): + break + log.append(counter) + + sorted_log = sorted(log) + print("medium: {}".format((sorted_log[499]+sorted_log[500])/2)) + plt.hist(log, bins=100) + plt.savefig('./hw1_12.png') + plt.show() + print(pla.w) \ No newline at end of file diff --git a/hw1_9.py b/hw1_9.py new file mode 100644 index 0000000..331d6ae --- /dev/null +++ b/hw1_9.py @@ -0,0 +1,120 @@ +# 26744.0, 27177.0, 26982.0 +# [99, 289.36156150772626, -1438.5724638894396, 1665.4574907561664, -1563.7272899602135, -988.4793846879909, -2412.181094351847, 1355.672859940388, -948.9745573599807, -384.40018958384206, 1279.5203042150952, -537.1648580135336, -807.3189828731862] + +import random +from datetime import datetime +import matplotlib.pyplot as plt + +class PLA(): + def __init__(self, data): + self.data = data + self.dim = len(self.data[0]['x']) + self.w = [0] * self.dim + + def iterate(self): + ''' + randomly picks an example (x_n, y_n) in every iteration. + updates wt if and only if w_t is incorrect on the example. + + Inputs: + None + Outputs: + mistake: bool. + ''' + index = random.randint(0, len(data)-1) + mistake = 1 if sign(dot(self.w, self.data[index]['x'])) != self.data[index]['y'] else 0 + if mistake: + self.update(index) + return mistake + + def update(self, index): + ''' + w_(t+1) = w_t + y_t*x_t + + Inputs: + index: which row need to use for updating weight + Outputs: + None + ''' + for i in range(self.dim): + self.w[i] = self.w[i] + self.data[index]['y'] * self.data[index]['x'][i] + +def read_file(): + ''' + read numbers from 'hw1_train.dat' + + Inputs: + None + Outputs: + data: dict list. each dict has ('x', 'y') pair + x is a list contains 12 numbers. + y is either 1 or -1. + ''' + with open('hw1_train.dat') as fp: + data = [] + lines = fp.readlines()[:-1] + for line in lines: + numbers = line.split() + x = [ float(i) for i in numbers[:-1] ] + x.insert(0,1) + y = int(numbers[-1]) + + data.append({ + 'x': x, + 'y': y, + }) + return data + +def dot(a, b): + ''' + dot product + + Inputs: + a: a list + b: a list. its length must be equal to len(a) + Outputs: + ans: a number + ''' + ans = 0 + assert len(a)==len(b) + for i in range(len(a)): + ans += a[i] * b[i] + return ans + +def sign(a): + ''' + positive || negative + + Inputs: + a: a number + Outputs: + ans: 1 or -1, means this is positive or negative + ''' + return 1 if a>0 else -1 + +if __name__ == '__main__': + data = read_file() + log = [] + for i in range(1000): + random.seed(datetime.now().timestamp()) + pla = PLA(data) + + counter = 0 + stopping_counter = 0 + while 1: + mistake = pla.iterate() + counter += 1 + if mistake: + stopping_counter = 0 + else: + stopping_counter += 1 + if stopping_counter == (5*len(data)): + break + log.append(counter) + + sorted_log = sorted(log) + print("medium: {}".format((sorted_log[499]+sorted_log[500])/2)) + plt.hist(log, bins=100) + plt.savefig('./hw1_9.png') + plt.show() + print(pla.w) \ No newline at end of file diff --git a/hw1_train.dat b/hw1_train.dat new file mode 100644 index 0000000..65b648e --- /dev/null +++ b/hw1_train.dat @@ -0,0 +1,257 @@ + 81.019756959203747 -0.24647068258400448 53.001506201026736 -4.8813938766354159 42.061094441343421 -9.9536086741920329 18.061001174379342 72.878121009181328 16.757591604840254 52.706566427130866 53.417805252705961 91.131736823895309 1 + 67.281901332808488 -3.4521095935884074 44.394048571163765 -6.4641765439286916 30.73343814024286 -14.561703488955343 14.793258428258412 57.997708970331225 13.155526635618273 43.452327330138139 40.889212235215247 75.71112320125242 1 + 88.047470516406648 8.2848167010917209 60.973078173489206 2.5414296529979521 50.355504137894314 -3.8851213618270215 26.157398209609177 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