Wszystkie pola: dissimilarity measure - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: THE MEASUREMENT OF THE ECONOMIC DISTANCE ON THE BASIS OF SYMBOLIC DATA
Autorzy:: Wilk, Justyna
Powiązania:: https://bibliotekanauki.pl/articles/655818.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:: economic distance
dissimilarity measure
symbolic data
regional research
Opis:: The economic distance defines a dissimilarity level between objects functioning in the economic space. It is one of the most important issues of spatial econometrics. However its measurement is difficult due to the definition, description and estimation problems. The objective of the paper is to indicate the role of symbolic data in describing the economic distance and also the way of its measurement using symbolic data analysis methods. A significance of the economic distance, measurement problems, symbolic data concept and dissimilarity measures, and also an empirical example were presented in the paper.
Źródło:: Acta Universitatis Lodziensis. Folia Oeconomica; 2014, 3, 302
0208-6018
2353-7663
Pojawia się w:: Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Effect of choice of dissimilarity measure on classification efficiency with nearest neighbor method
Autorzy:: Górecki, Tomasz
Powiązania:: https://bibliotekanauki.pl/articles/729668.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:: nearest neighbor method
discriminant coordinates
dissimilarity measures
estimators of classification error
Opis:: In this paper we will precisely analyze the nearest neighbor method for different dissimilarity measures, classical and weighed, for which methods of distinguishing were worked out. We will propose looking for weights in the space of discriminant coordinates. Experimental results based on a number of real data sets are presented and analyzed to illustrate the benefits of the proposed methods. As classical dissimilarity measures we will use the Euclidean metric, Manhattan and post office metric. We gave the first two metrics weights and now these measures are not metrics because the triangle inequality does not hold. Howeover, it does not make them useless for the nearest neighbor classification method. Additionally, we will analyze different methods of tie-breaking.
Źródło:: Discussiones Mathematicae Probability and Statistics; 2005, 25, 2; 217-239
1509-9423
Pojawia się w:: Discussiones Mathematicae Probability and Statistics
Dostawca treści:: Biblioteka Nauki

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