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Derginin Adı:
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Mediterranean Journal of Modeling and Simulation
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Cilt:
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2016/2
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Sayı:
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1
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Makale Başlık:
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Ensemble classi
cation methods for autism disordered speech
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Makale Alternatif Dilde Başlık:
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Alternatif dilde başlık bulunmamaktadır. There is no article title in another language.)
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Makale Eklenme Tarihi:
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26.09.2016
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Okunma Sayısı:
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1
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Makale Özeti:
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In this paper, we present the results of our investigation on Autism classifi
cation by applying ensemble classi
ers to disordered speech signals. The aim is to distinguish between Autism sub-classes by comparing an ensemble combining three decision methods, the sequential minimization optimization (SMO) algorithm, the random forests (RF), and the feature-subspace aggregating approach (Feating). The conducted experiments allowed a reduction of 30% of the feature space with an accuracy increase over the baseline of 8.66% in the development set and 6.62% in the test set.
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Alternatif Dilde Özet:
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Alternatif dilde abstract bulunmamaktadır. (There is no abstract in another language.)
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