from utility import Data, evaluate
import knn_models
import time
if __name__ == "__main__":
start_time = time.time()
data = Data()
data.pca_transform()
acc = []
for X_train, X_test, y_train, y_test in data.load():
knn = knn_models.SklearnkNNWithBallTree(5, X_train, y_train,
'inverse proportional')
acc.append(knn.score(X_test, y_test))
end_time = time.time()
evaluate(acc)
print('total time: %.4fs' % (end_time - start_time))
from utility import Data, evaluate
import svm_models
import time
if __name__ == "__main__":
start_time = time.time()
data = Data()
data.pca_transform(0.9)
acc = []
for X_train, X_test, y_train, y_test in data.load():
svm = svm_models.SklearnLinearSVC(X_train, y_train)
acc.append(svm.score(X_test, y_test))
end_time = time.time()
evaluate(acc)
print('total time: %.4fs' % (end_time-start_time))