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Add LLE kernel option #293
Merged
qbarthelemy
merged 21 commits into
pyRiemann:master
from
gabelstein:LLE_kernel_callable
Apr 15, 2024
Merged
Add LLE kernel option #293
qbarthelemy
merged 21 commits into
pyRiemann:master
from
gabelstein:LLE_kernel_callable
Apr 15, 2024
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qbarthelemy
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Apr 11, 2024
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Thanks @gabelstein for this improvement!
My major comment is that it is not necessary to add a new parameter kernel
: extending metric
should be enough.
Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>
qbarthelemy
reviewed
Apr 12, 2024
Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>
…yRiemann into LLE_kernel_callable
qbarthelemy
reviewed
Apr 15, 2024
Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>
…yRiemann into LLE_kernel_callable
qbarthelemy
approved these changes
Apr 15, 2024
Thx @gabelstein ! |
qbarthelemy
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that referenced
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Apr 17, 2024
* Adding Euclidean Alignment as implemented in the paper * Organizing code * Organizing code * resolving comments * prepare release 0.6 (#291) * Adapting TLCenter * update release and year * simplify code and complete doc * Add LLE kernel option (#293) * Add kernel option and tests * Update whatsnew.rst * Update whatsnew.rst * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com> * lint * improve whatsnew * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com> * linting * add none kernel test * might needed for flake8 * Update embedding.py * Delete .idea/workspace.xml * Update test_embedding.py * Update test_embedding.py * Apply suggestions from code review Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com> * change error * linting --------- Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com> * deleting 'euclidean.py' file * fixing flake8 errors * updating whatsnew file * move contrib to version 0.7 in whatsnew --------- Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com> Co-authored-by: Gabriel Wagner vom Berg <42769425+gabelstein@users.noreply.github.com>
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This adds a kernel option to LLE to make it more flexible.
Also, it allows for new parameter 'None' for n_neighbors and n_components to be more similar to e.g. KernelPCA from scikit-learn.