AttributeError: 'SupervisedDataSet' object has no attribute '_convertToOneOfMany'

使用pybrain构造神经网络，在执行官网代码时出错：

means = [(-1,0),(2,4),(3,1)]cov = [diag([1,1]), diag([0.5,1.2]), diag([1.5,0.7])]alldata = ClassificationDataSet(2, 1, nb_classes=3)for n in xrange(400):    for klass in range(3):        input = multivariate_normal(means[klass],cov[klass])        alldata.addSample(input, [klass])tstdata, trndata = alldata.splitWithProportion( 0.25 )trndata._convertToOneOfMany( )tstdata._convertToOneOfMany( )

报错：

AttributeError: 'SupervisedDataSet' object has no attribute '_convertToOneOfMany'

在代码中alldata被定义成ClassificationDataSet,官网查看后发现这个类确实有_convertToOneOfMany()方法。

在https://github.com/pybrain/pybrain/commit/2f02b8d9e4e9d6edbc135a355ab387048a00f1af中找到原因如下：

Now splitWithProporion uses numpy array indicies with numpy.random.permutation instead of for loop, before this change on large datasets this method was very slow, now its finish almost instant.

This commit breaks polymorphism: When called on an ClassificationDataSet (as shown in the tutorials) it no longer returns ClassificationDataSets but SupervisedDataSets.

执行

splitWithProporion后alldata返回的是SupervisedDataSets而不是ClassificationDataSet，而SupervisedDataSets没有_convertToOneOfMany方法。

解决办法：

http://stackoverflow.com/questions/27887936/attributeerror-using-pybrain-splitwithportion-object-type-changed/30869317#30869317

将上面代码改为：

tstdata_temp, trndata_temp = alldata.splitWithProportion(0.25)tstdata = ClassificationDataSet(2, 1, nb_classes=3)for n in xrange(0, tstdata_temp.getLength()):    tstdata.addSample( tstdata_temp.getSample(n)[0], tstdata_temp.getSample(n)[1] )trndata = ClassificationDataSet(2, 1, nb_classes=3)for n in xrange(0, trndata_temp.getLength()):    trndata.addSample( trndata_temp.getSample(n)[0], trndata_temp.getSample(n)[1] )

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