Releases: lutzhamel/popsom7
Release 7.0.0
This release now includes a Python version
R(version 7.0.0) Python(version 7.0.0)
What's Changed
- Popsom7 by @lutzhamel in #20
- edits by @lutzhamel in #21
Full Changelog: v6.0...v7.0.0
Release 6.0
- 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.minimal
object. 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.minimal
objects cannot be processed by any of the other functions in the POPSOM interface. - The
map.convergence
function provides details about the underlying convergence characteristics.
- The
- Bugfixes
- Most importantly the artificial limit of a minimum of 50 instances in the training
data has been removed.
- Most importantly the artificial limit of a minimum of 50 instances in the training
Release 5.2
Reworked the description of the package in order to reflect the capabilities of the package better.
Release 5.1
-
Something got rattled with the S3 interface in R 4.x. It no longer works the way it did in release 3.x. Therefore, I took the S3 interface out because I want the package to work with both 3.x and 4.x installations. Furthermore, the advantages of the S3 interface are incremental at best and I don't feel like debugging R internals.
-
Implemented a 'summary' function for map objects.
Release 5.0
Popsom 5.0 is a complete rarchitecting of the package. It includes the following:
- Support for two models:
- A self-organizing map model
- A centroid based clustering model
- Quality measures available for both models
- Streamlined S3 based API
- Easy access to the most important map and centroid data structures
- Powerful map visualization with centroid identification
- Extremely fast training algorithm based on ideas from tensor algebra
Release 4.3.1
Fixed code with the deprecated functions.
Release 4.3.0
This release introduces a decaying alpha value for the VSOM training algorithm fixing convergence problems at high learning rates. This release also deprecates a number of interface objects in order to get ready for the next release.
Release 4.0.1
fixed Fortran cross-platform issues
Release 4.0 (VSOM)
The biggest change in the 4.0 release of popsom is the inclusion of a vectorized version of the stochastic SOM training algorithm. This new training algorithm runs up to 10 times faster than the batch algorithm and between 50 to 100 times faster than the traditional stochastic training algorithm. Of course the precise numbers depend strongly on the kind of problem you are working on.
The SOM quality reporting functions have been made consistent with our recent publications:
see http://homepage.cs.uri.edu/faculty/hamel/pubs/
popsom 3.0.1
This is the current release in R, June 2016