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In the wrapper approach to feature subset selection, a search for an optimal set of features is made using the induction algorithm as a black box. The estimated future performance of the algorithm is the heuristic guiding the search. Statistical methods for feature subset selection including forward selection, backward elimination, and their stepwise(More)
The simple Bayesian classi er (SBC), sometimes called Naive-Bayes, is built based on a conditional independence model of each attribute given the class. The model was previously shown to be surprisingly robust to obvious violations of this independence assumption, yielding accurate classi cation models even when there are clear conditional dependencies. We(More)
The simple Bayesian classi er (SBC), sometimes called Naive-Bayes, is built based on a conditional independence model of each attribute given the class. The model was previously shown to be surprisingly robust to obvious violations of this independence assumption, yielding accurate classi cation models even when there are clear conditional dependencies. The(More)
Within this study we apply a speech emotion recognition engine on the detection of microsleep endangered sleepiness states. Current approaches in speech emotion recognition use low-level descriptors and functionals to compute brute-force feature sets. This paper describes an usually large feature set (45k) utilizing a broad pool of diverse elementary(More)
The aim of this study is to detect the occurrence of microsleep events in an overnight driving task. We propose a biosignal analysis method for the detection and extraction of microsleep events. This is achieved by employing blind source extraction method based on a cascaded nonlinear estimator to extract the relevant microsleep events. The cascaded(More)
This paper describes a general framework for detecting affective and energetic states based on prosody, articulation and speech quality related speech characteristics. The advantages of this realtime approach are that obtaining speech data is non obstrusive, free from sensor application and calibration efforts. The main part of the feature computation is(More)
In the wrapper approach to feature subset selection, a search for an optimal set of features is made using the induction algorithm as a black box. The estimated future performance of the algorithm is the heuristic guiding the search. Statistical methods for feature subset selection including forward selection, backward elimination, and their stepwise(More)
Periodogram and other spectral power estimation methods are established in quantitative EEG analysis. Their outcome in case of drowsy subjects fulfilling a sustained attention task is difficult to interpret. Two novel kind of EEG analysis based on pattern recognition were proposed recently, namely the microsleep (MS) and the alpha burst (AB) pattern(More)