Hi Sheila.
I think Peter got the right answer: load_svmlight_File yields a sparse Matrix
that you need to convert to an Array First.
Cheers, andy
--
Diese Nachricht wurde von meinem Android-Mobiltelefon mit K-9 Mail gesendet.
Sheila the angel <[email protected]> schrieb:
Hi Andreas,
there is no difference between two data sets (except scaling).
But that is not a issue. Whenever I try to read data from libsvm format file
using function load_svmlight_file("file_name") it gives me object which is
different then default in tutorials.
for example in tutorial-
http://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html
# I replaced iris = datasets.load_iris() by
X_train, y_train = load_svmlight_file("iris.scale")
X =X_train[:,:2] # iris.data[:, :2] # we only take the first two features.
Y = y_train
x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
AttributeError: min not found
On Wed, May 30, 2012 at 7:13 PM, Andreas Mueller <[email protected]>
wrote:
Hi Sheila.
It would help if you could say what the difference between the two datasets is.
Given the name "iris.scale" I would assume that it is somehow scaled,
either using zero mean, unit variance, between 0 and 1 or l2 normalized.
Have you tried using Scaler on the data to see what you get?
Cheers,
Andy
Am 30.05.2012 19:10, schrieb Sheila the angel:
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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