A resource-allocating network for function interpolation
Neural Computation
A function estimation approach to sequential learning with neural networks
Neural Computation
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Letters: Convex incremental extreme learning machine
Neurocomputing
Risk-sensitive loss functions for sparse multi-category classification problems
Information Sciences: an International Journal
No-reference image quality assessment using modified extreme learning machine classifier
Applied Soft Computing
Online adaptive radial basis function networks for robust object tracking
Computer Vision and Image Understanding
Engineering Applications of Artificial Intelligence
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
A new pruning heuristic based on variance analysis of sensitivity information
IEEE Transactions on Neural Networks
A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks
IEEE Transactions on Neural Networks
Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks
IEEE Transactions on Neural Networks
Fast learning fully complex-valued classifiers for real-valued classification problems
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Information Sciences: an International Journal
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
A meta-cognitive sequential learning algorithm for neuro-fuzzy inference system
Applied Soft Computing
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
A novel self-constructing Radial Basis Function Neural-Fuzzy System
Applied Soft Computing
Hi-index | 0.01 |
This paper addresses sequential learning algorithm for self-adaptive resource allocation network classifier. Our approach makes use of self-adaptive error based control parameters to alter the training data sequence, evolve the network architecture, and learn the network parameters. In addition, the algorithm removes the training samples which are similar to the stored knowledge in the network. Thereby, it avoids the over-training problem and reduces the training time significantly. Use of misclassification information and hinge loss error in growing/learning criterion helps in approximating the decision function accurately. The performance evaluation using balanced and imbalanced data sets shows that the proposed algorithm generates minimal network with lesser computation time to achieve higher classification performance.