lsa.py 文件源码

def __init__(self, n_features=100, transform=True, classifier='lsvm', kernel='rbf', n_neighbors=5):
        self.n_features = n_features
        self.transform = transform
        self.clf_type = classifier
        if classifier == 'lsvm':
            self.clf = LinearSVC()
        elif classifier == 'svm':
            self.clf = SVC(kernel=kernel, probability=True)
        elif classifier == 'knn':
            self.clf = KNeighborsClassifier(n_neighbors=n_neighbors, algorithm='brute', metric='cosine')