Autoencoders are data-specific compression algorithms learned automatically from examples. The predominant approach has been to construct single large global models that cover the domain. However, training and evaluating of increasing size comes at price additional time computational cost. Conditional computation, sparsity, model pruning techniques can reduce these costs while maintaining perfo...

In the diagnosis of epileptic seizures, classification is an important step that directly affects results. Visual inspection Electroencephalogram (EEG) a relatively common analytic method epilepsy, but it costly, time-consuming and relies on experiences doctor. Therefore, development efficient accurate seizure automatic system suitable for clinical has become urgent task. order to better solve ...

Naive Bayes induction algorithm is very popular in classification field. Traditional method for dealing with numeric data is to discrete numeric attributes data into symbols. The difference of distinct discredited criteria has significant effect on performance. Moreover, several researches had recently employed the normal distribution to handle numeric data, but using only one value to estimate...

This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computatio...

The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance variables which are concerned as the important parameters of TIPP and recommend trading...

This paper presents an evaluation of an ensemble–based system that participated in the English and Spanish lexical sample tasks of SENSEVAL-2. The system combines decision trees of unigrams, bigrams, and co–occurrences into a single classifier. The analysis is extended to include the SENSEVAL-1 data.

This paper presents an evaluation of an ensemble–based system that participated in the English and Spanish lexical sample tasks of SENSEVAL-2. The system combines decision trees of unigrams, bigrams, and co–occurrences into a single classifier. The analysis is extended to include the SENSEVAL-1 data.

current inversion condition leads to incorrect operation of current based directional relay in power system with series compensated device. application of the intelligent system for fault direction classification has been suggested in this paper. a new current directional protection scheme based on intelligent classifier is proposed for the series compensated line. the proposed classifier uses ...

An approach to increase adaptability of a recognition system, which can recognise 10 elementary gestures and be extended to sign language recognition, is proposed. In this work, recognition is done by firstly extracting a motion gradient orientation image from a raw video input and then classifying a feature vector generated from this image to one of the 10 gestures by a sparse Bayesian classif...