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## Support Vector Machine | |
import numpy as np | |
train_f1 = x_train[:,0] | |
train_f2 = x_train[:,1] | |
train_f1 = train_f1.reshape(90,1) | |
train_f2 = train_f2.reshape(90,1) | |
w1 = np.zeros((90,1)) | |
w2 = np.zeros((90,1)) | |
epochs = 1 | |
alpha = 0.0001 | |
while(epochs < 10000): | |
y = w1 * train_f1 + w2 * train_f2 | |
prod = y * y_train | |
print(epochs) | |
count = 0 | |
for val in prod: | |
if(val >= 1): | |
cost = 0 | |
w1 = w1 - alpha * (2 * 1/epochs * w1) | |
w2 = w2 - alpha * (2 * 1/epochs * w2) | |
else: | |
cost = 1 - val | |
w1 = w1 + alpha * (train_f1[count] * y_train[count] - 2 * 1/epochs * w1) | |
w2 = w2 + alpha * (train_f2[count] * y_train[count] - 2 * 1/epochs * w2) | |
count += 1 | |
epochs += 1 |
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What is cost used for?
And wouldn't lines 29 and 30 produce an error, since train_f1[count] and y_train[count] are numbers, whereas 2 * 1/epochs * w1 is a vector?
Thanks in advance!