def problem_1c(n=500):
algorithmList = [
'Perceptron', 'Perceptron with margin', 'Winnow', 'Winnow with margin',
'AdaGrad'
]
bestParaList = {500: [(1, 0), (0.03, 1), (1.1, 0), (1.1, 2.0), (0.25, 1)], \
1000: [(1, 0), (0.03, 1), (1.1, 0), (1.1, 2.0), (0.25, 1)]}
t = Trainer()
d = t.data_generator(l=10,
m=100,
n=n,
number_of_instances=50000,
noise=False)
x, y = d['x'], d['y']
initDict = initDictGenerator(n=t.n)
color = 'rgbyk'
for idx in range(len(algorithmList)):
algorithm = algorithmList[idx]
algorithmInit = initDict[algorithm]
if n in bestParaList:
lr, mg = bestParaList[n][idx]
else:
lr, mg = bestParaList[500][idx]
algorithmInit['learning rate'] = [lr]
algorithmInit['margin'] = [mg]
t.learning(algorithm,
x,
y,
initDict={algorithm: algorithmInit},
times=1)
t._unpack_resDict(lr, mg)
plt.plot(t.mistake_list, color[idx])
plt.legend(algorithmList, loc='best')
plt.title('Plots for n = %s' % n)
plt.show()
def problem_2_plot():
algorithmList = [
'Perceptron', 'Perceptron with margin', 'Winnow', 'Winnow with margin',
'AdaGrad'
]
bestParaList = {
40: [(1, 0), (0.25, 1), (1.1, 0), (1.1, 2.0), (1.5, 1)],
80: [(1, 0), (0.03, 1), (1.1, 0), (1.1, 2.0), (0.25, 1)],
120: [(1, 0), (0.03, 1), (1.1, 0), (1.1, 2.0), (0.25, 1)],
160: [(1, 0), (0.03, 1), (1.1, 0), (1.1, 2.0), (0.25, 1)],
200: [(1, 0), (0.25, 1), (1.1, 0), (1.1, 2.0), (1.5, 1)]
}
record = {}
for algorithm in algorithmList:
record[algorithm] = []
for n in range(40, 240, 40):
print()
t = Trainer()
d = t.data_generator(l=10,
m=20,
n=n,
number_of_instances=50000,
noise=False)
x, y = d['x'], d['y']
initDict = initDictGenerator(n=t.n)
color = 'rgbyk'
for idx in range(len(algorithmList)):
algorithm = algorithmList[idx]
algorithmInit = initDict[algorithm]
if n in bestParaList:
lr, mg = bestParaList[n][idx]
else:
lr, mg = bestParaList[500][idx]
algorithmInit['learning rate'] = [lr]
algorithmInit['margin'] = [mg]
t.learningWithStop(algorithm,
x,
y,
initDict={algorithm: algorithmInit},
times=1)
print(len(t.resDict[lr, mg][3]))
t._unpack_resDict(lr, mg)
record[algorithm].append(t.mistake_list[-1])
i = 0
for algorithm in algorithmList:
plt.plot(range(40, 240, 40), record[algorithm], color[i])
i += 1
plt.legend(algorithmList, loc='best')
plt.xlabel('Number of total features')
plt.xticks(range(40, 240, 40))
plt.ylabel('Total Mistakes before stop')
#plt.title('Plots for n = %s'%n)
plt.savefig('p2plot.png', dpi=144)
plt.show()
