我在下面使用这个数据集，并试图找到数据集的支持向量机。我也有我的代码和错误。

http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html#sklearn.datasets.load_breast_cancer

import numpy as np
from sklearn import svm,datasets
breastcancer = datasets.load_breast_cancer()
#print(breastcancer)
everydata = breastcancer.data
#print(everydata)
everytarget = breastcancer.target
traindata = []
traintarget = []
testdata = []
testclasses = []
#Class 0 data separtion
for i in range(0,140):
    traindata.append(everydata[i])
    traintarget.append(everytarget[i])
for i in range(140,212):
    testdata.append(everydata[i])
#Class 1 data separation
for i in range(212,357):
    traindata.append(everydata[i])
    traintarget.append(everytarget[i])
for i in range(357,569):
    testdata.append(everydata[i])
traindata = np.concatenate((everydata[:140, :],everydata[212:357, :]),axis=0)
traintarget = np.concatenate((everydata[:140],everydata[212:357]),axis=0)
testdata = np.concatenate((everydata[140:212, :],everydata[357:569, :]),axis=0)
print(len(traindata))
print(traintarget)
print(testdata)
dd = svm.SVC(kernel='linear')
dd.fit(traindata,traintarget)
decide = dd.predict(testdata)
print(decide)

为什么我收到此错误是我的串联不正确。结果应该在最后输出 0 和 1。