A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation.
Mario MartínEnrique ContrerasJavier BéjarGennaro EspositoDiógenes ChávezSilvio GlusmanUlises CortésPablo RudomínPublished in: Frontiers Neuroinformatics (2014)
Keyphrases
- machine learning
- text classification
- pattern recognition
- machine learning algorithms
- decision trees
- supervised machine learning
- spinal cord
- machine learning methods
- feature selection
- classification accuracy
- support vector
- supervised learning
- support vector machine
- data mining
- model selection
- supervised classification
- image classification
- classification algorithm
- machine learning approaches
- structured learning
- higher order
- random selection
- statistical methods
- information extraction