用作索引的数组必须是整数(或布尔)类型 [英] Arrays used as indices must be of integer (or boolean) type
问题描述
错误是这样的:
Traceback (most recent call last):
File "NearestCentroid.py", line 53, in <module>
clf.fit(X_train.todense(),y_train)
File "/usr/local/lib/python2.7/dist-packages/scikit_learn-0.13.1-py2.7-linux-i686.egg/sklearn/neighbors/nearest_centroid.py", line 115, in fit
variance = np.array(np.power(X - self.centroids_[y], 2))
IndexError: arrays used as indices must be of integer (or boolean) type
代码是这样的:
distancemetric=['euclidean','l2']
for mtrc in distancemetric:
for shrkthrshld in [None]:
#shrkthrshld=0
#while (shrkthrshld <=1.0):
clf = NearestCentroid(metric=mtrc,shrink_threshold=shrkthrshld)
clf.fit(X_train.todense(),y_train)
y_predicted = clf.predict(X_test.todense())
我使用的是scikit-learn
包,X-train
,y_train
是LIBSVM格式,X
是特征:值对,y_train
是目标/标签,X_train
是CSR矩阵格式,shrink_threshold
不支持CSR稀疏矩阵,所以我将 .todense()
添加到 X_train
,然后我得到了这个错误,谁能帮我解决这个问题?非常感谢!
I am using scikit-learn
package, X-train
, y_train
are in LIBSVM format, X
is the feature:value pair, y_train
is the target/label, X_train
is in CSR matric format, the shrink_threshold
does not support CSR sparse matrix, so I add .todense()
to X_train
, then I got this error, could anyone help me fix this? Thanks a lot!
推荐答案
我在使用 Pystruct pystruct.learners.OneSlackSSVM
时遇到了类似的问题.
I had a similar problem using the Pystruct pystruct.learners.OneSlackSSVM
.
发生这种情况是因为我的训练标签是浮点数,而不是整数.就我而言,这是因为我使用 np.ones 初始化了标签,而没有指定 dtype=np.int8.希望有帮助.
It occured because my training labels were floats, in stead of integers. In my case, it was because I initialized the labels with np.ones, without specifying dtype=np.int8. Hope it helps.
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