openModeller Desktop 1.0.8 - Changelog

What's new in openModeller Desktop 1.0.8:

February 3rd, 2009

· Local modelling plugin is now using version 0.7.0 of the openModeller library (which includes a new algorithm based on Artificial Neural Networks), multiple projections in the same experiment are now supported, new option to automatically split input points into testing and training according to a given proportion, new option in preferences to generate maps in Arc/Info ASCII Grid format (byte or floating point representation), display testing and training points using different shapes (circles for training points, triangles for testing points), display internal and external tests separately in the report, MSVC DLLs are now always installed on Windows, removed locale options (Portuguese and Afrikaans) that were not being updated.

What's new in openModeller Desktop 1.0.6:

November 26th, 2007

· Improved mapping capabilities - you can now specify occurrence symbol size and colour, and overlay a context layer (such as country boundaries) on your output map.
· Experiments run in their own thread.- this makes for a more responsive user interface and you can look at completed models whilst the experiment is still running.
· Web Service modelling improvements - improvement have been made to allow better job progress reporting when running as a web sevice.
· Absence modelling is now supported - previous versions of openModellerDesktop did not handle absence data properly so absence modelling was not available.
· GBIF Rest Data Fetcher (work sponsored by GBIF with our thanks!) - it is now possible to retrieve occurrence data using the new GIF Rest query service. The data fetcher has also had various cosmetic and useability improvements, and now functions as a wizard.
· New algorithms - openModeller Desktop now ships with two new algorithms (Support Vector Machines and Bioclim Score).
· Thresholding tool - you can now compute 'hotspot' models showing the predicted species count per cell by aggregating many model outputs into a single raster file. The threshold tool can also be used for 'concensus' modelling where many algorithms are used for a single species and all the resulting probability distribution maps are combined to provide a map indicating where most algorithms are in agreement that a species will ocurr at a given cell.