PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Wykorzystanie naiwnego algorytmu Bayes'a w zadaniu klasyfikacji podatników

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
PL
Abstrakty
EN
Resolving tasks of classification for real-world problems became possible because of rising and development of more efficient IT systems. The goal of described solution in the paper is also real-world problem of finding these taxpayers, who could have problems with observance of the tax law. The solution is based on classification of persons, by assigning them to group with or without taxations problems. Usage of Naive Bayes Algorithm for classification, choosing appropriate attributes describing problem, building and applying the model led to reaching above described goal with better accuracy in comparison to “intuitive” choice and gave more accurate results, than some other known classification algorithms used for such domain. It results in more accurate typing of tax payers for controlling purposes of tax authorities.
Rocznik
Tom
Strony
143--152
Opis fizyczny
Bibliogr. 10 poz., rys.
Twórcy
autor
  • Zachodniopomorski Uniwersytet Technologiczny w Szczecinie, Wydział Informatyki
Bibliografia
  • [1] David Hand, Heikki Mannila, Padhraic Smith, Principles of Data Mining, Massachusetts Institute of Technology, 2001
  • [2] Jiawei Han, Micheline Kamber, Data Mining: Concepts and Techniques second edition, Morgan Kaufmann Publishers, 2006
  • [3] Evangelos Trantaphyllou, Giovanni Felici, Data Mining and Knowledge Discovery approaches based on rule induction techniques, Springer Science Business Media, 2006
  • [4] Ian H.Witten, eibe Frank: Data Mining Practical Machine Learning Tools and Techniques, Morgan Kaufmann, 2005
  • [5] Oracle Data Mining Concepts 11g Release 1 (11.1), Oracle Corp., 2005-2007
  • [6] Oracle Data Miner 11.1.0.1.0, Oracle Corp., 2005-2007
  • [7] Oracle Database Documentation Library 11g Release 1 (11.1), Oracle Corp., 2008
  • [8] Ramez Elmasri, Shamkant B. Navathe: Fundamentals of Database Systems, Addison-Wesley, 2004
  • [9] Bernhard Schoelkopf, Alexander J.Smola: Learning with kernels, Support Vector Machines, Regularization, Optimization, and Beyond, The MIT Press, 2002
  • [10] Pawlak Zdzisław, Some issues on rough sets, Springer Science, 2005
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS3-0014-0060
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.