ValueError: The number of classes has to be greater than one (python)

Question

在 fit 中传递 x,y 时，出现以下错误：

追溯（最近调用最后）：

File "C:/Classify/classifier.py", line 95, in

train_avg, test_avg, cms = train_model(X, y, "ceps", plot=True)
File "C:/Classify/classifier.py", line 47, in train_model

clf.fit(X_train, y_train) File "C:\Python27\lib\site-packages\sklearn\svm\base.py", line 676, in fit raise ValueError("The number of classes has to be greater than" ValueError: The number of classes has to be greater than one.

下面是我的代码：

def train_model(X, Y, name, plot=False):
"""
    train_model(vector, vector, name[, plot=False])

    Trains and saves model to disk.
"""
labels = np.unique(Y)

cv = ShuffleSplit(n=len(X), n_iter=1, test_size=0.3, indices=True, random_state=0)

train_errors = []
test_errors = []

scores = []
pr_scores = defaultdict(list)
precisions, recalls, thresholds = defaultdict(list), defaultdict(list), defaultdict(list)

roc_scores = defaultdict(list)
tprs = defaultdict(list)
fprs = defaultdict(list)

clfs = []  # for the median

cms = []

for train, test in cv:
    X_train, y_train = X[train], Y[train]
    X_test, y_test = X[test], Y[test]

    clf = LogisticRegression()
    clf.fit(X_train, y_train)
    clfs.append(clf)

Answer 1

您可能在训练集中只有一个唯一的 class 标签。如错误消息所述，您需要在数据集中至少有两个唯一的 classes。例如，您可以运行 np.unique(y) 查看数据集中唯一的 class 标签是什么。

Answer 2

没错。您的最后一列（标签）只有一种类型（分类）。你应该至少有两个。例如;如果您的标签决定您是否必须卸载，则标签列应该有卸载和不卸载或（0 或 1）。

ValueError: The number of classes has to be greater than one (python)

ValueError: The number of classes has to be greater than one (python)

classification

svm

python-2.7

scikit-learn