def test_reformat(self):
negatives=[[3,1],[-4,-5],[10,-1]]
positives=[[3,6],[-1,0],[2,3]]
(X,y)=MySVM.reformat(positives,negatives)
self.assertEqual(y,[1,1,1,0,0,0])
self.assertEqual(X,[[3,6],[-1,0],[2,3],[3,1],[-4,-5],[10,-1]])
def test_reformat(self):
negatives = [[3, 1], [-4, -5], [10, -1]]
positives = [[3, 6], [-1, 0], [2, 3]]
(X, y) = MySVM.reformat(positives, negatives)
self.assertEqual(y, [1, 1, 1, 0, 0, 0])
self.assertEqual(X,
[[3, 6], [-1, 0], [2, 3], [3, 1], [-4, -5], [10, -1]])
def test_easy(self):
#y>x
negatives=[[3,1],[-4,-5],[10,-1]]
positives=[[3,6],[-1,0],[2,3]]
testpairs=[[3,1],[3,6],[3,2],[3,4],[3,2.2],[3,3.5]]
testanswers=[0,1,0,1,0,1]
results = MySVM.train_test(positives,negatives,testpairs)
for i in range(len(testpairs)):
print "Test "+str(i)+" : "+str(testanswers[i])+" : "+str(results[i])
self.assertEqual(results[i],testanswers[i])
def main():
#default, two class, 100 samples, 20 features
#X, y = datasets.make_classification(n_samples=510)
X, y = datasets.load_svmlight_file("data")
#X = np.array([[1,2], [2,2], [3,2], [4,2], [5,2], [6,2],\
# [1,0], [2,0], [3,0], [4,0], [5,0], [6,0]])
#y = np.array([1,1,1,0,1,1,0,0,0,1,0,0])
#processing_y(y)
X = X.toarray()
#X_train = X[:100]
#y_train = y[:100]
#X_test = X[100:]
#y_test = y[100:]
#X_train = X
#y_train = y
#X_test = np.array([[7,2],[8,-2],[9,5],[10,0]])
#y_test = np.array([1,-1,1,-1])
X_train = X[:500]
y_train = y[:500]
X_test = X[500:510]
y_test = y[500:510]
clf = MySVM(kernel=my_kernel_2, c=1)
clf.fit(X_train, y_train)
print "total iterate times: %d" % clf.rounds
print "here are multipliers:"
print clf._multipilers
#print "the w is ", clf.get_w()
#print "the b is ", clf._b
acount = 0.0
#print clf.y
#for i in range(4):
for i in range(10):
yp = clf.predict(X_test[i])
print yp, y_test[i]
if yp == y_test[i]:
acount += 1
print "Accuracy: ", acount/10
print "The alphas is :", len(clf.support_mislabeled)
print clf.support_mislabeled
def test_easy(self):
#y>x
negatives = [[3, 1], [-4, -5], [10, -1]]
positives = [[3, 6], [-1, 0], [2, 3]]
testpairs = [[3, 1], [3, 6], [3, 2], [3, 4], [3, 2.2], [3, 3.5]]
testanswers = [0, 1, 0, 1, 0, 1]
results = MySVM.train_test(positives, negatives, testpairs)
for i in range(len(testpairs)):
print "Test " + str(i) + " : " + str(testanswers[i]) + " : " + str(
results[i])
self.assertEqual(results[i], testanswers[i])
