Hi everyone!
I'm new to scikit and I'm gettin trouble with some visualization method!!!
What I wanna do is visualize in a plot/graph, something like this:
http://scikit-learn.org/stable/auto_examples/exercises/plot_iris_exercise.html
Essentialy I would see the background color based on my training set to see how
the SVM will classify my new elements. It could be a line or a color in the
bacground.
Everything is ok if I will use just two features! I can obtain XX and YY but,
in my case, I have 6 features and I don't know hot to do the grid!! Almost all
the example use just two features from the iris dataset...There is one that use
four but essentially it applies a PCA in order to reduce the features to two
and so, let me say, I kind of cheating in order to get the graph....
Actually my code is the following:
....graph = pylab.scatter(X_train[:,0],X_train[:,2],c=colors, zorder= 10)ax =
grafico.axesax.set_xlabel('Feature_1')ax.set_ylabel('Feature_2')pylab.scatter(clf.support_vectors_[:,0],clf.support_vectors_[:,2],marker
= 'x', c='y',s=200,zorder= 1, label='Support Vector')pylab.legend(loc = 'lower
right')pylab.show()....
Where X_train contain six features and not just two!
Thanks to everyone!!!
Solimyr ------------------------------------------------------------------------------
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