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classifier.py
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classifier.py
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from sklearn import tree
from sklearn import svm
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
def DecisionTree(x_train, y_train, x_test, criterion_name):
model = tree.DecisionTreeClassifier(criterion = criterion_name)
model.fit(x_train, y_train)
y_test = model.predict(x_test)
return y_test
def SVM(kernel_name,x_train,y_train,x_test,x_train_num,x_test_num):
model = svm.SVC(kernel=kernel_name)
for i in range(10):
valid_set_size = 0.10
XTrain, XTest, yTrain, yTest = train_test_split(x_train_num, y_train, test_size=valid_set_size)
model.fit(XTrain, yTrain)
yPred = model.predict(XTest)
print('the validation set size: ' + str(valid_set_size))
score = accuracy_score(yTest, yPred)
print('the validation accuracy: ' + str(score))
y_test = model.predict(x_test_num)
return y_test