| create.linear.toy.data | R Documentation |
Based on Weston (2000) Feature Selection for SVMs.
Creates matrix X and vector Y with six dimensions out of 202 relevant and
equal probability of y = 1 or -1.
With a prob of 0.7 we draw xi = y * norm(i, 1) for i = 1, 2, 3 and
xi = norm(0, 1) for i = 4, 5, 6.
Otherwise: xi = norm(0, 1) for i = 1, 2, 3 and xi = y * norm(i - 3, 1)
for i = 4, 5, 6.
All other features are noise.
create.linear.toy.data(n)
n |
|
list(X = [Matrix], Y = [vector], orig.features = logical)
Other Artificial Datasets:
clonetask(),
create.hypersphere.data(),
create.linear.data(),
create.regr.task(),
task.add.permuted.cols(),
task.add.random.cols()
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