Displaying similar documents to “Improving feature selection process resistance to failures caused by curse-of-dimensionality effects”

Conceptual base of feature selection consulting system

Pavel Pudil, Jana Novovičová, Petr Somol, Radek Vrňata (1998)

Kybernetika

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The paper briefly reviews recent advances in the methodology of feature selection (FS) and the conceptual base of a consulting system for solving FS problems. The reasons for designing a kind of expert or consulting system which would guide a less experienced user are outlined. The paper also attempts to provide a guideline which approach to choose with respect to the extent of a priori knowledge of the problem. The methods discussed here form the core of the software package being developed...

Experiments with two Approaches for Tracking Drifting Concepts

Koychev, Ivan (2007)

Serdica Journal of Computing

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This paper addresses the task of learning classifiers from streams of labelled data. In this case we can face the problem that the underlying concepts can change over time. The paper studies two mechanisms developed for dealing with changing concepts. Both are based on the time window idea. The first one forgets gradually, by assigning to the examples weight that gradually decreases over time. The second one uses a statistical test to detect changes in concept and then optimizes the...

Combined classifier based on feature space partitioning

Michał Woźniak, Bartosz Krawczyk (2012)

International Journal of Applied Mathematics and Computer Science

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This paper presents a significant modification to the AdaSS (Adaptive Splitting and Selection) algorithm, which was developed several years ago. The method is based on the simultaneous partitioning of the feature space and an assignment of a compound classifier to each of the subsets. The original version of the algorithm uses a classifier committee and a majority voting rule to arrive at a decision. The proposed modification replaces the fairly simple fusion method with a combined classifier,...

Combining adaptive vector quantization and prototype selection techniques to improve nearest neighbour classifiers

Francesc J. Ferri (1998)

Kybernetika

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Prototype Selection (PS) techniques have traditionally been applied prior to Nearest Neighbour (NN) classification rules both to improve its accuracy (editing) and to alleviate its computational burden (condensing). Methods based on selecting/discarding prototypes and methods based on adapting prototypes have been separately introduced to deal with this problem. Different approaches to this problem are considered in this paper and their main advantages and drawbacks are pointed out along...

Comparison of speaker dependent and speaker independent emotion recognition

Jan Rybka, Artur Janicki (2013)

International Journal of Applied Mathematics and Computer Science

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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...