Displaying similar documents to “Algorithms for Classification based on k-NN.”

Experiments with two Approaches for Tracking Drifting Concepts

Koychev, Ivan (2007)

Serdica Journal of Computing

Similarity:

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

Similarity:

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...

Improving feature selection process resistance to failures caused by curse-of-dimensionality effects

Petr Somol, Jiří Grim, Jana Novovičová, Pavel Pudil (2011)

Kybernetika

Similarity:

The purpose of feature selection in machine learning is at least two-fold - saving measurement acquisition costs and reducing the negative effects of the curse of dimensionality with the aim to improve the accuracy of the models and the classification rate of classifiers with respect to previously unknown data. Yet it has been shown recently that the process of feature selection itself can be negatively affected by the very same curse of dimensionality - feature selection methods may...

Application of Classification Methods to a Problem Related to Specific Groups of E-Government Users

Angelova, Vesela, Eskenazi, Avram (2008)

Serdica Journal of Computing

Similarity:

This paper was partly supported by ELOST – a SSA EU project – No 27287. One of the important tasks of the EU ELOST project on E-government and Low Socio-Economic Status Groups (LSG) was to compare experts’ opinions on fundamental problems of the subject. This papers shows how the application of specific classification methods to experts’ formalized answers could lead to some non-trivial and objective conclusions about interdependencies and the interrelation between e-government...