Displaying similar documents to “Variance reduction trends on `boosted' classifiers.”

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...

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...

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...

A variant of gravitational classification

Tomasz Górecki, Maciej Luczak (2014)

Biometrical Letters

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In this article there is proposed a new two-parametrical variant of the gravitational classification method. We use the general idea of objects' behavior in a gravity field. Classification depends on a test object's motion in a gravity field of training points. To solve this motion problem, we use a simulation method. This classifier is compared to the 1NN method, because our method tends towards it for some parameter values. Experimental results on different data sets demonstrate an...

Lexical Error Compensation in Handwritten-Based Mathematical Information Retrieval

Ahmadi, Seyed Ali, Youssef, Abdou

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Entering mathematical queries, in general, can be a demanding task. Mathematical notation is two-dimensional and cannot be easily typed with a standard QWERTY keyboard. Handwriting appears to be the most intuitive and promising method to express mathematical queries. Recognition technology for handwritten mathematical notation has never been applied in math search. The objective of this research is to design and implement an automated symbol-recognition error compensation system for...