/home/dogus/anaconda2/lib/python2.7/site-packages/sklearn/utils/validation.py:429:DataConversionWarning：带有输入dtype int8的数据被normalize函数转换为float64 . warnings.warn（msg，_DataConversionWarning）Traceback（最近一次调用最后一次）：文件“assignment5.py”，第171行，在knn.fit（X_train，y_train）文件“/home/dogus/anaconda2/lib/python2.7/ site-packages / sklearn / neighbors / base.py“，第775行，in fit check_classification_targets（y）文件”/home/dogus/anaconda2/lib/python2.7/site-packages/sklearn/utils/multiclass.py“，第172行，在check_classification_targets中引发ValueError（“未知标签类型：％r”％y_type）ValueError：未知标签类型：'continuous-multioutput'
1 - 'continuous-multioutput'是什么意思？
2-'DataConversionWarning'是至关重要的吗？
# TODO: Just like your preprocessing transformation, create a PCA
# transformation as well. Fit it against your training data, and then
# project your training and testing features into PCA space using the
# PCA model's .transform() method.
pca = PCA(n_components=2, svd_solver='auto')
pca.fit(X_train,y_train)
X_train = pca.transform(X_train)
y_train = pca.transform(y_train)
X_test = pca.transform(X_test) # should i transform tests?
y_test = pca.transform(y_test)
print X_train,"----",y_train
knn = KNeighborsClassifier(n_neighbors=9)
knn.fit(X_train,y_train)
输入：打印X_train：[[0.0669871 0.01377793] [-0.00501622 -0.06383211] ... [0.13320158 0.02851528] [-0.06106258 -0.02458237]]
print y_train：[[0.02357345 0.01313697] [0.02357345 0.01313697] ... [0.02357345 0.01313697] [0.78585397 0.12070276]]
主要问题是如何解决这个连续多输出错误？谢谢 .