A new polynomial-time algorithm for linear programming
Combinatorica
Applied multivariate statistical analysis
Applied multivariate statistical analysis
Neural Networks
Universal approximation using radial-basis-function networks
Neural Computation
Probabilistic neural network architecture for high-speed classification of remotely sensed imagery
Telematics and Informatics - Special issue: Neural networks and artificial intelligence technologies for space applications
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
Advanced algorithms for neural networks: a C++ sourcebook
Advanced algorithms for neural networks: a C++ sourcebook
Feature minimization within decision trees
Computational Optimization and Applications
Time-series forecasting using GA-tuned radial basis functions
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Feature Selection Via Mathematical Programming
INFORMS Journal on Computing
Radial Basis Function Networks in Nonparametric Classification and Function Learning
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Cycling in linear programming problems
Computers and Operations Research
Evolving RBF neural networks for time-series forecasting with EvRBF
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
Kernel class-wise locality preserving projection
Information Sciences: an International Journal
A Sieving ANN for Emotion-Based Movie Clip Classification
IEICE - Transactions on Information and Systems
Relevant feature selection from EEG signal for mental task classification
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Hybridization of the probabilistic neural networks with feed-forward neural networks for forecasting
Engineering Applications of Artificial Intelligence
A three phase approach for mental task classification using EEG
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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We propose a two-stage model for detecting nonlinear patterns in discriminant problems and for solving the problem. The model deploys a Linear Programming Based Discriminator (LPBD) in stage one for treating linear patterns and a Probabilistic Neural Network (PNN) in stage two for handling nonlinear patterns. The LPBD in stage one divides the decision space into a clear zone where observations are (almost) linearly separable and a gray zone where nonlinear patterns are more likely to occur. The PNN in stage two analyzes the gray zone and determines whether a significant nonlinear patterns exist in the observations. Our goal is to avoid using a nonlinear model unless the PNN strongly suggests so to maintain good interpretability and avoid overfitting. Our computational study demonstrates the effectiveness of the two-stage model in both classification accuracy and computational efficiency.