CompLearn is a suite of simple-to-use utilities that you can use to apply compression techniques to the process of discovering and learning patterns. The compression-based approach used is powerful because it can mine patterns in completely different domains. It can classify musical styles of pieces of music and identify unknown composers. It can identify the language of bodies of text. It can discover the relationships between species of life and even the origin of new unknown viruses such as SARS. Other uncharted areas are up to you to explore. In fact, this method is so general that it requires no background knowledge about any particular classification. There are no domain-specific parameters to set and only a handful of general settings. Simplicity at your fingertips.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Arbuckle, Tom: Studying software evolution using artefacts’ shared information content (2011)
- Cilibrasi, Rudi L.; Vitányi, Paul M.B.: A fast quartet tree heuristic for hierarchical clustering (2011)
- Granados, Ana; Cebrián, Manuel; Camacho, David; Rodríguez, Francisco B.: Evaluating the impact of information distortion on normalized compression distance (2008)
- Mantaci, Sabrina; Restivo, Antonio; Sciortino, Marinella: Distance measures for biological sequences: some recent approaches (2008)