The effect to diagnostic accuracy of decision tree classifier of fuzzy and k-NN based weighted pre-processing methods to diagnosis of erythemato-squamous diseases

Digital Signal Processing: A Review Journal

Volumn 16, Issue 6, 2006, Pages 922-930

  Polat, Kemal ^a   Güneş, Salih ^a  

^a SELCUK UNIVERSITY   (Turkey)

Author keywords

Decision tree classifier; Erythemato squamous; Fuzzy weighted pre processing; k Fold cross validation; k NN based weighting pre processing

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION THEORY; DISEASES; NEURAL NETWORKS; TREES (MATHEMATICS);

DECISION TREE CLASSIFIER; ERYTHEMATO-SQUAMOUS; FUZZY WEIGHTED PRE-PROCESSING; K-FOLD CROSS VALIDATION; K-NN BASED WEIGHTING PRE-PROCESSING;

FUZZY SETS;

EID: 33751185331     PISSN: 10512004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dsp.2006.04.007     Document Type: Article

References (9)

1. ftp://ftp.ics.uci.edu/pub/machine-learning-databases, last accessed April 20, 2006
2. Demiroz G., Govenir H.A., and Ilter N. Learning differential diagnosis of eryhemato-squamous diseases using voting feature intervals. Artific. Intell. Med. 13 (1998) 147-165
3. Govenir H.A., and Emeksiz N. An expert system for the differential diagnosis of erythemato-squamous diseases. Expert Syst. Appl. 18 (2000) 43-49
4. Ubeyli E.D., and Guler I. Automatic detection of erythemato-squamous diseases using adaptive neuro-fuzzy inference systems. Comput. Biol. Med. 35 (2005) 421-433
5. Nanni L. An ensemble of classifiers for the diagnosis of erythemato-squamous diseases. Neurocomputing 69 (2006) 842-845
6. K. Polat, S. Şahan, S. Güneş, A new method to medical diagnosis: Artificial immune recognition system (AIRS) with fuzzy weighted pre-processing and application to ECG arrhythmia, Expert Syst. Appl. (2005), in press
7. Mitchell M.T. Machine Learning (1997), McGraw-Hill, Singapore
8. Quinlan J.R. Induction of decision trees. Mach. Learn. 1 (1986) 81-106
9. http://www.cs.cmu.edu/~schneide/tut5/node42.html, last accessed April 20, 2006