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View Code? Open in Web Editor NEWA Julia Package for Machine Learning on the Manifold of Positive Definite Matrices
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A Julia Package for Machine Learning on the Manifold of Positive Definite Matrices
License: Other
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Hi, I recommend installing CompateHelper.jl : https://github.com/JuliaRegistries/CompatHelper.jl
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This error may appear at execution time
the first time an SVM model is fitted or is passed to the cvAcc function.
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Using cvAcc with ENLR, it may occur that lambda_min_ratio is wrongly estimated, resulting in an error from GLMNet (TaskFailedException: cannot specify both lambda and lambda_min_ratio). This could be avoided by passing the correct value of lambda_min_ratio.
This error is not raised when fitting directly ENLR, it is raised only with cvAcc.
Minimal example:
using PosDefManifoldML
PTr, PTe, yTr, yTe=gen2ClassData(20, 190, 38, 200, 40, 0.1)
cvAcc(ENLR(Fisher), PTr, yTr) # raise TaskFailedException
cvAcc(ENLR(Fisher), PTr, yTr; lambda_min_ratio=1e-4) # works
fit(ENLR(Fisher), PTr, yTr) # works also
My guess is that _getDim
(in tools.jl) is not returning the same dimension as the dimension of the ℍVector, when projected in the tangent space (done in _getFeat_fit
), resulting in this error message in GLMNet (https://github.com/JuliaStats/GLMNet.jl/blob/master/src/GLMNet.jl#L225)
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