8000 DOC Added references to plot_ica_blind_source_separation & plot_ica_vs_pca.py by V-Rang · Pull Request #30786 · scikit-learn/scikit-learn · GitHub
[go: up one dir, main page]
Skip to content

DOC Added references to plot_ica_blind_source_separation & plot_ica_vs_pca.py #30786

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 6 commits into from
Closed

DOC Added references to plot_ica_blind_source_separation & plot_ica_vs_pca.py #30786

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
d499b93
placed reference to pca vs ica example
V-Rang Feb 8, 2025
6ab15e8
references to other
V-Rang Feb 8, 2025
40d298d
reference to pca performance on signal detection
V-Rang Feb 8, 2025
a6a568b
Merge branch 'main' into feature
V-Rang Feb 8, 2025
765c022
Merge branch 'main' into feature
V-Rang Feb 8, 2025
b1399d6
modifications made
V-Rang Feb 10, 2025
File filter

Filter by extension

Filter by extension 8000
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 0 additions & 2 deletions doc/modules/decomposition.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,6 @@ data based on the amount of variance it explains. As such it implements a
* :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_lda.py`
* :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_fa_model_selection.py`


.. _IncrementalPCA:

Incremental PCA
Expand Down Expand Up @@ -770,7 +769,6 @@ components with some sparsity:
* :ref:`sphx_glr_auto_examples_decomposition_plot_ica_vs_pca.py`
* :ref:`sphx_glr_auto_examples_decomposition_plot_faces_decomposition.py`


.. _NMF:

Non-negative matrix factorization (NMF or NNMF)
Expand Down
1 change: 0 additions & 1 deletion examples/decomposition/plot_ica_blind_source_separation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,6 @@
ie. what is played by each instrument. Importantly, PCA fails
at recovering our `instruments` since the related signals reflect
non-Gaussian processes.

"""

# Authors: The scikit-learn developers
Expand Down
95CE
1 change: 0 additions & 1 deletion examples/decomposition/plot_ica_vs_pca.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,6 @@
after whitening by the variance corresponding to the PCA vectors (lower
left). Running ICA corresponds to finding a rotation in this space to
identify the directions of largest non-Gaussianity (lower right).

"""

# Authors: The scikit-learn developers
Expand Down
Loading
0