Hi,
sometimes I still encounter some problems with the transition from mvpa
to mvpa2. This time, I would like to run a Searchlight on an artificial
dataset. Previously that could be done like this:
from sklearn.datasets import make_classification
X,y = make_classification(n_samples=55, n_features=630, n_classes=2)
ds = MaskedDataset(samples=X, labels=y, chunks=np.arange(y.size))
cv = CrossValidatedTransferError(
TransferError(LinearCSVMC()),
OddEvenSplitter())
sl = Searchlight(cv, radius=5)
In mvpa2 I could do the same
ds = Dataset(X)
ds.targets = y
ds.chunks = np.arange(55)
but the sphere_searchlight requires a 'space' parameter. Here I don't
have real neighbor-space relations. It can be completely random or
neighbors in the np.array. How would you define that for a synthetic
dataset?
Thanks in advance,
Matthias
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