Ryan Curtin
c8eb3dceac
* Add pipeline to documentation homepage. * Fix for mobile devices. * Add little pipelines to go at the top of each page. * Overhaul index page. * Overhaul README to remove redundant material. * Add installation documentation. * Update pipelines. * Allow nesting of deeper details. * Add a pipeline to the top of the load/save page. * Add prerequisites link to main pipeline. * Add better but not finished sidebar. * Add a couple new documentation pages. * Fix URLs in svg. * Incremental checkin. * Fix Youtube URLs. * Incremental checkin. * Minor fixes. * Add first pass at evaluation/deployment pages. * Minor spacing and link fixes. * Flesh out a number of additional pages and write basic compilation documentation. * Fix some minor issues, and add Docker deployment page (not totally finished yet). * Add developer documentation landing page. * Hopefully getting close to the final set of changes here. * Remove this documentation for now. * Fix a few links, and the size of the sidebar. * Fix some additional links. * Fix a bunch more links. * Fix another link that now has a better place. * Refactor test-docs.sh to handle documentation that is a standalone program. * Fix file exclusions. * Fully qualify typename. * Update name of file. * Fix syntax error. * Remove files that are not meant to be compiled. * Also skip the quickstart. * Move quickstart entry to the top. * Remove gray coloring of binding documentation. * Update name of sidebar link. * Update to working link. * Fix Wikipedia anchor.
44 lines
1.3 KiB
Markdown
44 lines
1.3 KiB
Markdown
<object data="../img/pipeline-top-3.svg" type="image/svg+xml" id="pipeline-top">
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</object>
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# Transformations
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Once data is [loaded](load_save.html) and any necessary
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[preprocessing and feature extraction](preprocessing.md) is done,
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one of mlpack's transformations can be used to transform data into a
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new space.
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*Note: this section is under construction and not all functionality is
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documented yet.*
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## Matrix decompositions
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Decompose a matrix into two or more components.
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* [AMF](methods/amf.md): alternating matrix factorization
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* [NMF](methods/nmf.md): non-negative matrix factorization
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## Linear transformations
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Linearly map a matrix onto a new basis, optionally performing dimensionality
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reduction.
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* [PCA](methods/pca.md): principal components analysis
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* [RADICAL](methods/radical.md): an independent components analysis technique
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## Metric learning techniques
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Learn a [distance metric](core/distances.md) based on a data matrix.
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* [LMNN](methods/lmnn.md): large margin nearest neighbor
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* [NCA](methods/nca.md): neighborhood components analysis
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## Coding techniques
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Encode data points in a matrix as a combination of points in a dictionary.
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* [LocalCoordinateCoding](methods/local_coordinate_coding.md): local coordinate
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coding with dictionary learning
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* [SparseCoding](methods/sparse_coding.md): sparse coding with dictionary
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learning
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