The main goal of this library is to work as a bridge between the Machine Learning and the Image Processing fields. Weka supports several standard data mining tasks, more specifically, data preprocessing, clustering, classification, regression, visualization, and feature selection.ease of use due to its graphical user interfaces.a comprehensive collection of data preprocessing and modeling techniques.portability, since it is fully implemented in the Java programming language and thus runs on almost any modern computing platform.freely availability under the GNU General Public License.As described on their wikipedia site, the advantages of Weka include: It contains a collection of visualization tools and algorithms for data analysis and predictive modeling, together with graphical user interfaces for easy access to this functionality. Weka (Waikato Environment for Knowledge Analysis) can itself be called from the plugin. The Trainable Weka Segmentation is a Fiji plugin and library that combines a collection of machine learning algorithms with a set of selected image features to produce pixel-based segmentations.
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