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Fast Gaussian Naïve Bayes for searchlight classification analysis
Marlis Ontivero-Ortega
, Agustin Lage-Castellanos
,
Giancarlo Valente
,
Rainer Goebel
, Mitchell Valdes-Sosa
*
*
Corresponding author for this work
Auditory Neurosc. & Statistical Modeling
Visual Neurosc. & Brain–Computer Interf.
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peer-review
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INIS
accuracy
100%
classification
100%
vectors
100%
levels
66%
comparative evaluations
66%
gain
66%
implementation
66%
speed
66%
testing
33%
algorithms
33%
applications
33%
cost
33%
errors
33%
brain
33%
corrections
33%
multivariate analysis
33%
coverings
33%
gold
33%
Keyphrases
Searchlight
100%
Classification Analysis
100%
Nave Bayes
100%
Support Vector Machine
50%
Lateral Occipital Complex
33%
Searchlight Analysis
33%
Statistical Significance
16%
Meta-analysis
16%
Large Set
16%
Functional Magnetic Resonance Imaging
16%
Cluster Analysis
16%
Metaanalysis
16%
Whole Brain
16%
Neural Activity
16%
Computational Cost
16%
Classification Algorithms
16%
Error Rate
16%
Multivariate Pattern Analysis
16%
Activation Study
16%
Multinomial Naïve Bayes
16%
Permutation Method
16%
Cluster Level
16%
Multiple Comparison Correction
16%
Matrix Laboratory (MATLAB)
16%
Small Region
16%
Biochemistry, Genetics and Molecular Biology
Support Vector Machine
100%
Gaussian Distribution
100%
Bayesian Learning
33%
Functional Magnetic Resonance Imaging
33%
Earth and Planetary Sciences
Support Vector Machine
100%