Semi-naive bayesian classifier

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 482 LNAI, Issue , 1991, Pages 206-219

  Kononenko, Igor ^a  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

Author keywords

(In)Dependence of events; Approximations of probabilities; Bayesian classifier; Machine learning

Indexed keywords

ARTIFICIAL INTELLIGENCE; DIAGNOSIS; MEDICAL PROBLEMS;

(IN)DEPENDENCE OF EVENTS; BAYESIAN CLASSIFIER; CLASSIFICATION ACCURACY; MEDICAL DIAGNOSTICS; NAIVE BAYES; NAIVE BAYESIAN CLASSIFIER; TWO DOMAINS;

LEARNING SYSTEMS;

EID: 85031799549     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/BFb0017015     Document Type: Conference Paper

References (11)

1. Cestnik B. (1990) Estimating Probabilities: A Crucial Task in Machine Learning, Proc. European Conference on Artificial Intelligence 90, Stockholm, August 1990.
2. Cestnik, B., Kononenko, I., Bratko, I. (1987) ASSISTANT 86 : A Knowledge Elicitation Tool for Sophisticated Users. In: I. Bratko, N. Lavraf (eds.), Progress in Machine learning. Wilmslow, England: Sigma Press.
3. Good I.J. (1950) Probability and the weighing of evidence. London: Charles Griffin.
4. Kononenko, I. (1989) ID3, sequential Bayes, naive Bayes and Bayesian neural networks. Proc. 4th European Working Session on Learning, Montpellier, France, December 1989, pp.91-98.
5. Kononenko, I. (1990) Comparison of inductive and naive Bayesian learning approaches to automatic knowledge acquisition. In: B. Wielinga et al. (eds.) Current Trends in Knowledge Acquisition, Amsterdam: IOS Press.
6. Kononenko, I. & Bratko, I. (1991) Information Based Evaluation Criterion for Classifier’s Performance. Machine Learning, Vol.6, pp.67-80 (in press).
7. Pirnat V., Kononenko I., Jane T., Bratko I. (1989) Medical Estimation of Automatically Induced Decision Rules, Proc. of 2nd Europ. Conf. on Artificial Intelligence in Medicine, City University, London, August 29-31 1989, pp.24-36.
8. Smyth P. & Goodman R.M. (1990) Rule Induction Using Information Theory. In: G.Piarersky & W.Frawley (eds.) Knowledge Discovery in Databases, MIT Press.
9. Vadnal A. (1979) Elementary Introduction to Probability Calculus (in Slovene), Driavna zalozba Slovenije, Ljubljana.
10. Van de Velde (1989) IDL, or Taming the Multiplexer, Proc. 4th European Working Session on Learning, Montpellier, France, December 1989, pp.211-225.
11. Wan S.J. &, Wong S.K.M. (1989) A Measure for Concept Dissimilarity and its Applications in Machine Learning, Proc. Int. Conf. on Computing and Information, Toronto North, Canada, May 23-27 1989.