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Bioinformatics Engineering Program Uppsala University School of Engineering

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Bioinformatics Engineering Program

Uppsala University School of Engineering

UPTEC X 09 033 Date of issue 2009-10

Author

Jonas Gisterå

Title (English)

Comparing classification accuracy between different classification algorithms

Title (Swedish)

Abstract

In this study the performance of four classification algorithms; k-Nearest Neighbors, Linear Discriminant Analysis, Support Vector Machine and Random Forest was analysed when applied on SELDI-TOF-MS data. No conclusions could be made about any algorithm performing better than the rest of the algorithms. The classification results seem to be more dependent of the datasets than the classification algorithm used.

Keywords

Classification algorithms, data mining, mass spectrometry, SELDI-TOF-MS, supervised classification, feature selection.

Supervisors

Michal Lysek

MedicWave AB

Scientific reviewer

Tomas Olofsson

Department of Engineering Sciences, Uppsala University

Project name Sponsors

Language

English

Security

ISSN 1401-2138

Classification

Supplementary bibliographical information Pages

41

Biology Education Centre Biomedical Center

Husargatan 3 Uppsala Box 592 S-75124 Uppsala Tel +46 (0)18 4710000 Fax +46 (0)18 555217

References

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