An Efficient Implementation of Kohonen's Self-Organizing Maps (SOMs) with Starburst Visualizations
Overview
Kohonen's self-organizing maps with a number of distinguishing features: (1) An efficient, single threaded, stochastic training algorithm inspired by ideas from tensor algebra. Provides significant speedups over traditional single-threaded training algorithms. No special accelerator hardware required (see doi:10.1007/978-3-030-01057-7_60). (2) Automatic centroid detection and visualization using starbursts. (3) Two models of the data: (a) a self organizing map model, (b) a centroid based clustering model. (4) A number of easily accessible quality metrics for the self organizing map and the centroid based cluster model (see doi:10.1007/978-3-319-28518-4_4).
- Renamed the functions in the interface to avoid collisions with S3 functions within the R environment. We know that this is another renaming of the POPSOM interface and we apologize for any inconvenience. We expect that the interface is now stable for the foreseeable future.
- New features:
- The
map.minimalobject. This is an object that only contains the trained neurons and nothing else. This is an appropriate model when POPSOM is used as a preprocessing step and no other model information is needed. Note thatmap.minimalobjects cannot be processed by any of the other functions in the POPSOM interface. - The
map.convergencefunction provides details about the underlying convergence characteristics. - Bugfixes
- Most importantly the artificial limit of a minimum of 50 instances in the training data has been removed.
From NEWS.md in the release
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- Help pages
- 9
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 78%
- Help pages citing references
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- RR 4.4.0 released · 2024-04-24
- archivedRemoved from CRAN2023-09-11issues were not corrected in time Use of Fortran RANDOM_NUMBER
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 6.02021-12-20 · diff ↗ ·
removed 8 exports
map, fitted, marginal, position, predict, significance, starburst, summaryadded 9 exports
map.build, map.fitted, map.convergence, map.marginal, map.position, map.predict, map.significance, map.starburst, map.summary - 5.22021-07-09 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 5.1
- 5.02020-12-09 · diff ↗ ·
removed 9 exports
map.build, map.convergence, map.embed, map.topo, map.starburst, map.projection, map.significance, map.neuron, map.marginaladded 7 exports
map, starburst, fitted, predict, position, significance, marginal - 4.3.12020-08-29 · diff ↗
- 4.3.02020-07-22 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 4.2.12019-06-03 · diff ↗
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 4.22017-06-01 · diff ↗ ·
removed 2 exports
map.embedding, map.accuracyadded 4 exports
map.embed, map.topo, map.neuron, map.marginal
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- RR 3.4.0 released · 2017-04-21
- 4.0.12016-08-14 · diff ↗
- 4.02016-08-13 · diff ↗ ·
removed 1 export
pattern:.added 7 exports
map.build, map.convergence, map.embedding, map.accuracy, map.starburst, map.projection, map.significance - RR 3.3.0 released · 2016-05-03
- 3.0.12015-07-22 · diff ↗
- RR 3.2.0 released · 2015-04-16
- RR 3.1.0 released · 2014-04-10
- 2.32013-10-01 · diff ↗
- RR 3.0.0 released · 2013-04-03
- 2.22013-03-12
- RR 2.15.0 released · 2012-03-30
Package metadata
- First published
- 2013-03-12
- Total releases
- 13 / 13 yrs
- License
- GPL-3 OSI
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