Comments (1)
I fixed diffusion map, now it should work properly. Here is an example:
using ManifoldLearning, Plots, LinearAlgebra, StatsBase
X, _ = ManifoldLearning.spirals(1000, 0.02);
c = standardize(UnitRangeTransform, mapslices(norm, X, dims=1) |> vec, dims=1)
scatter3d(X[1,:], X[2,:], X[3,:], zcolor=c, legend=:none, ms=3., camera=(15.,15.))
R = transform(fit(DiffMap, X, α=0.5, t=5, ε=0.002))
scatter(R[1,:], R[2,:], zcolor=c, legend=:none, ms=3.)
from manifoldlearning.jl.
Related Issues (20)
- Tag a new version? HOT 14
- Fit / transform interface for embeddings HOT 2
- Isomap transform fails with "Empty collection" error HOT 2
- Unexpected size of output of Isomap transform HOT 5
- Is diffusion map working? HOT 3
- MultivariateStats.jl and ManifoldLearning.jl
- Custom knn function not working? HOT 2
- TagBot trigger issue HOT 5
- MethodError for `connected_components` HOT 2
- DiffMap-error : k not defined HOT 5
- allow diffusion map to take as input a Gram matrix? HOT 3
- [PkgEval] ManifoldLearning may have a testing issue on Julia 0.4 (2015-02-13)
- Isomap nnType: Method error HOT 3
- OutOfMemoryError() HOT 2
- Connected components HOT 2
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- Stackoverflow Question about this package
- Isomap not working in master HOT 1
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from manifoldlearning.jl.