Thanks Peter,
it helps. But just wondering why load_svmlight_file() gives sparse matrix
(CSR format) and a numpy array!!
Is there any other way to use load_svmlight_file() return object directly
for analysis (without using X_train =X_train.toarray() )
On Wed, May 30, 2012 at 7:24 PM, Peter Prettenhofer <
[email protected]> wrote:
> Sheila,
>
> ``load_svmlight_file`` gives you a sparse matrix (CSR format) and a
> numpy array.
>
> You can convert the CSR matrix to a numpy array using::
>
> X_train = X_train.toarray()
>
> Please check if X_train.shape == iris.data.shape.
>
> Hope this helps!
>
> best,
> Peter
>
> 2012/5/30 Sheila the angel <[email protected]>:
> > Hi all,
> > I am trying to read libsvm format data 'iris.scale'
> > (from
> http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/iris.scale
> > ) as
> >
> > from sklearn.datasets import load_svmlight_file
> > X_train, y_train = load_svmlight_file('iris.scale')
> >
> > I thought this will give same format as
> >
> > from sklearn import datasets
> > iris = datasets.load_iris()
> >
> > Though y_train is same format as iris.target but X_train is not in same
> > format as iris.data !!!
> >
> > How can I read a libsvm format file same as datasets.load_iris()
> >
> > Thanks
> > --
> > Sheila
> >
> >
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>
>
> --
> Peter Prettenhofer
>
>
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