Hi, I am using scikit 0.11 for classification task.
I would like to test svm after Isomap reduction on my dataset, previously
splitted into a training/test set with StratifiedKFold.
Is it correct this procedure?
isomap = manifold.Isomap(n_neighbors, n_components).fit(x_train)
iso_train = isomap.transform(x_train)
iso_test = isomap.transform(x_test)
# SVM code
.
.
.
In other words, is the test set correctly mapped on the reduced space induced
with respect to the training set?
Should I use isomap on the whole dataset and then split it into training and
test set?
Thank you in advance!
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