Feature reduction using a RBF network for classification of learning styles in first year engineering students
When having a large number of variables in the input of an Artificial Neural Network (ANN), there are different problems in the design, structure and performance of the network itself. Feature reduction is the technique of selecting a subset of 'relevant' features for building robust learn...
Guardado en:
Autor principal: | Velez-Langs,Oswaldo |
---|---|
Lenguaje: | English |
Publicado: |
Universidad de Tarapacá.
2014
|
Materias: | |
Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052014000100013 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Network Intrusion Detection Based on Extended RBF Neural Network With Offline Reinforcement Learning
por: Manuel Lopez-Martin, et al.
Publicado: (2021) -
Differential Evolution Evolved RBFNN based automated recognition of Traffic Sign Images
por: Manasa R., et al.
Publicado: (2021) -
Multi-Ship Control and Collision Avoidance Using MPC and RBF-Based Trajectory Predictions
por: Myron Papadimitrakis, et al.
Publicado: (2021) -
A Novel Method for Multivariant Pneumonia Classification Based on Hybrid CNN-PCA Based Feature Extraction Using Extreme Learning Machine With CXR Images
por: Md. Nahiduzzaman, et al.
Publicado: (2021) -
Classification of sponge city construction modes based on regional features
por: Xin Zhao, et al.
Publicado: (2021)