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  1. Journal of Applied Sciences
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  3. 1755-1761
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Journal of Applied Sciences

Year: 2010 | Volume: 10 | Issue: 16 | Page No.: 1755-1761
DOI: 10.3923/jas.2010.1755.1761

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Authors


C.M. Bentaouza

Country: Algeria

M. Benyettou

Country: Algeria

Keywords


  • one versus rest
  • multiclass
  • microscopy
  • Medical image
  • supervised learning
Research Article

Support Vector Machines for Brain Tumours Cells Classification

C.M. Bentaouza and M. Benyettou
This research is a study applied to the supervised classification of brain tumours by a method resulting from the artificial intelligence which is the Support Vector Machines. The artificial intelligence quickly moved these last decades, with the evolution of the cerebral imagery to diagnose certain diseases such as the brain tumours by techniques like magnetic resonance imagery in order to treat this disease by the surgery and microscopy to detect the type and the rank of the tumour. The results obtained by the Support Vector Machines are satisfactory from the point of view of time of learning and convergence, which have in particular tendency to learn data too much, thus providing good performances in generalization. On the other hand the Support Vector Machines give automatically a reliable result.
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How to cite this article

C.M. Bentaouza and M. Benyettou, 2010. Support Vector Machines for Brain Tumours Cells Classification. Journal of Applied Sciences, 10: 1755-1761.

DOI: 10.3923/jas.2010.1755.1761

URL: https://scialert.net/abstract/?doi=jas.2010.1755.1761

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