Hi Johnson.
Please direct all scikit-learn related questions to the scikit-learn
mailing list (see CC), or ask a question on stackoverflow.com with the
scikit-learn tag.
What is the problem you are having with the example on the website?
Andy
On 03/29/2014 09:53 PM, Johnson Lee wrote:
Dear Andreas,
My name is Johnson Lee. I have a question about semi-supervised
classification. Could you please give me any help?
I am using LabelSpreading in scikit-learn to perform semi-supervised
classification for the digit data set and then would like to compare
this classification with SVM; however, I meet some problem. As I am a
very beginner of Python, it is a big challenge for me to implement the
semi-supervised classification with LabelSpreading using the following
example from scikit-learn.
from sklearn import datasets
from sklearn.semi_supervised import LabelSpreading
label_prop_model = LabelSpreading()
iris = datasets.load_iris()
random_unlabeled_points = np.where(np.random.random_integers(0, 1,
size=len(iris.target)))
labels = np.copy(iris.target)
labels[random_unlabeled_points] = -1
label_prop_model.fit(iris.data, labels)
...
LabelSpreading(...)
Could you please give me a full example for semi-supervised
classification with LabelSpreading?
Thanks for your attention!
Best wishes!
Johnson Lee
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