Cluster based rule discovery model for enhancement of government's tobacco control strategy
Exploring novel features and decision rules to identify cardiovascular autonomic neuropathy using a hybrid of wrapper-filter based feature selection
Hybrid wrapper-filter approaches for input feature selection using maximum relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA)
Smokers' characteristics and cluster based quitting rule discovery model for enhancement of government's tobacco control systems
A constraint-based evolutionary learning approach to the expectation maximization for optimal estimation of the hidden Markov model for speech signal modeling
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