Details

Autor(en) / Beteiligte

• Frank, Eibe
• Hall, Mark
• Trigg, Len
• Holmes, Geoffrey
• Witten, Ian H.

Titel

Data mining in bioinformatics using Weka

Ist Teil von

• Bioinformatics, 2004-10, Vol.20 (15), p.2479-2481

Ort / Verlag

Oxford: Oxford University Press

Erscheinungsjahr

2004

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection—common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. Availability: http://www.cs.waikato.ac.nz/ml/weka