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Erschienen in:
1996 | OriginalPaper | Buchkapitel
Automatic Segmentation by Decision Trees
verfasst von : Tomàs Aluja-Banet, Eduard Nafria
Erschienen in: COMPSTAT
Verlag: Physica-Verlag HD
Enthalten in: Professional Book Archive
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We present a system for automatic segmentation by decision trees, able to cope with large data sets, with special attention to stability problems. Tree-based methods are a statistical operation for automatic learning from data, its main characteristic is the simplicity of the obtained results. It uses a recursive algorithm which can be very costly for large data sets and it is very dependent on data, since small fluctuations on data may cause a big change in the tree-growing process. First our purpose has been to define data diagnostics to prevent internal instability in the tree growingprocess before a particular split has been made. Then we study the complexity of the algorithm and its applicability to big data sets.