Thanks Luca, I tried your suggestion but I am still getting that error. It
seems that the problem is causing because of boolean mask operations done on
numpy array inside precision_recall_fscore_support function() - ref[1]. Still
not sure though.
[1]
http://stackoverflow.com/questions/26778500/valueerror-too-many-boolean-indices-for-a-n-600-array-float
From: lucapug...@gmail.com
Date: Mon, 13 Apr 2015 16:04:51 +0000
To: scikit-learn-general@lists.sourceforge.net
Subject: Re: [Scikit-learn-general] Help: Getting ValueError
@precision_recall_fscore_support
I do not know if this is related to your problem but you should avoid mutable
default argument. Try to replace labels with a tuple. Or assign its default
value inside the function.
On Mon, Apr 13, 2015, 17:30 namma igloo <nammaig...@outlook.com> wrote:
Hi,
I'm new to sklearn and trying out python-crfsuit example [1] on my own data and
following the example code, I'm getting -@precision_recall_fscore_support
method: ValueError: too many boolean indices
I must note that this method is called by [classification_report] function
which I'm calling with following signature:
classification_report( y_true_combined, y_pred_combined,
labels = [class_indices[cls] for cls in tagset], target_names = tagset )
I do not get any error if I omit the optional parameters 'labels' and
'target_names'. So I am not sure if the issue is because of values of those two
parameters or somewhere else.
I have pasted here [2] the values of all four variables supplied to
classification_report.I'll appreciate in any help in troubleshooting this issue.
[1]
http://nbviewer.ipython.org/github/tpeng/python-crfsuite/blob/master/examples/CoNLL%202002.ipynb[2]
http://pastebin.com/qaq7Kf1u
Thanks
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