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A new approach to classification with the least number of features
Sascha Klement,
Thomas Martinetz
Institute of Neuro- and Bioinformatics
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Computer Science
classification result
100%
Feature Extraction
100%
Feature Selection
100%
Learning System
100%
Machine Learning
100%
Preprocessing Step
100%
Neuroscience
Functional Magnetic Resonance Imaging
100%
Support Vector Machine
100%
Medicine and Dentistry
Feature Extraction
100%
Functional Magnetic Resonance Imaging
100%
Biochemistry, Genetics and Molecular Biology
Functional Magnetic Resonance Imaging
100%
Support Vector Machine
100%