python中的数组形状错误

Question

I am trying to implement SVM for a dataset I found online.The features_test,features_train,labels_test,labels_train are python lists of tuples.I did the below to convert it into numpy arrays.But clf.fit is giving me the below error.

File "ebola.py", line 47, in <module>
clf.fit(features_train_numpy,labels_train_numpy)
File "/usr/lib64/python2.7/site-packages/sklearn/svm/base.py", line 151, in fit
y = self._validate_targets(y)
File "/usr/lib64/python2.7/site-packages/sklearn/svm/base.py", line 514, in _validate_targets
y_ = column_or_1d(y, warn=True)
File "/usr/lib64/python2.7/site-packages/sklearn/utils/validation.py", line 551, in column_or_1d
raise ValueError("bad input shape {0}".format(shape))
ValueError: bad input shape (2923, 9)

Code is as below

features_train_numpy = np.asarray(features_train)
labels_train_numpy= np.asarray(labels_train)
features_test_numpy = np.asarray(features_test)
labels_test_numpy= np.asarray(labels_test)
from sklearn.svm import SVC
temp = 100
clf=SVC(C=temp,kernel="rbf")
clf.fit(features_train_numpy,labels_train_numpy)`

Answer 1

Even from the error itself it is easy to notice that your labels matrix is two-dimensional, while it should be 1D vector. It should contain on i'th position - label of i'th example. In your case it looks like each sample has 9 labels, which is not supported by sklearn SVM.