所以这是我的代码：
我有一个features数组和一个labels数组，用于训练model.pkl
但是当我想在模型中添加single sample时，我会看到warning。
from sklearn import tree
from sklearn.externals import joblib
features = [[140, 1], [130, 1], [150, 0], [170, 0]]
labels = [0, 0, 1, 1]
# Here I train the model with the above arrays
clf = tree.DecisionTreeClassifier()
clf = clf.fit(features, labels)
joblib.dump(clf, 'model.pkl')
# Now I want to train the model with a new single sample
clf = joblib.load('model.pkl')
clf = clf.fit([130, 1], 0) # WARNING MESSAGE HERE!!
这是warning：
/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py:386:
DeprecationWarning:
Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19.
Reshape your data either using X.reshape(-1, 1)
if your data has a single feature or X.reshape(1, -1)
if it contains a single sample. DeprecationWarning)
我已经阅读了this。 但似乎我的例子不同。
我如何每次只训练一个样本的模型？
谢谢