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Update #1
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Make use of the BLAS GEMV operation in `enet_coordinate_descent` instead of using DOT in a `for`-loop. Go ahead and use GEMV with both non-transposed and transposed arrays. Previously we have had issues with the vendored BLAS and GEMV on transposed arrays, but this attempts to use GEMV on transposed arrays anyways. Hopefully we can make them work as well. As GEMV and DOT in a `for`-loop are both semantically equivalent, this is a reasonable change to make. Though GEMV likely uses a multithreaded approach unlike our application of DOT in a serial loop here. In BLAS implementations that do use threads for DOT, we can expect that GEMV will make better usage of those threads and avoid unnecessary setup and teardown costs that DOT in a `for`-loop is likely to incur (possibly in each iteration of the `for`-loop).
[MRG+2] DOC data centering in PCA
* add governance doc * add links to docs * minor formatting, more links * Update doc/governance.rst fix broken link Co-Authored-By: amueller <[email protected]> * Apply suggestions from code review Co-Authored-By: amueller <[email protected]> * reframed with call for vote. I think this is good. * make it easier to call a vote. * Update doc/governance.rst rephrasing Co-Authored-By: amueller <[email protected]> * link governance from the about page instead on documentation.rst
* enforce deterministic output in kernel PCA * add tests and update whats new * replace state by rng * simplified assert * avoid copy * clarify tests * remove now useless comment * use rng as seed everywhere
* Delete wrapper function optics around OPTICS optics () is a simple wrapper around the OPTICS class which instantiates the class and calls fit. This wrapper exists for DBSCAN or K-Means but not for all clustering methods. For code homogeneity, I am deleting this function. * delete optics wrapper from cluster module list Previous commit forgot to delete the optics wrapper from the cluster module list. So the test testing the presence of modules failed.
…rays (#13240) * adding argument check for the case spare=True and missing_values=0 issue #12750 * missing indicator: handle case array is sparse and missing values==0 issue #12750 * fix flake8 issues * remove empty lines * remove sparse==True and missing_value==0 case; handle `transform` method * remove blankline * separate out test for missing_value==0 and sparse input * remove spurious blank lines * added what's new entry * fixing lint issues * remove redundant code * fix issue number in "what's new" * move duplicate code to _validate_input * fix test for transform method * remove nested if conditions
* ENH fused types in isotonic_regression * make X drive computation dtype in IsotonicRegression * preserve current behaviour if transform w/o fit * thoroughly check sample weights; avoid storing dtype explicitly * consistent testing and behavior * misc * update what's new * fix for interp1d upcast on old scipy * flake8 remove blank line sorry, i'm rusty * add failing test * FIX dtype bug in _make_unique
…s not yet observed (#13280)
…egy is stratified (#13266)
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