Artifacts using weka-dev version 3.9.4

Trainable Segmentation plugin for Fiji.

The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

The implementation of the pixel classification algorithm, that is used the Labkit image segmentation plugin for Fiji.

Components Ext

Trainable segmentation features implemented with imglib2.

incubator

Contains modularized (jena-based) matchers that can be used to quickly assemble matching systems.

Helper class for internet related operations.

Executable Scripts

Mecj