The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 54-143
Full Name: John Sanford
Position: Professor
Age: ON
Sex: Male
Address: Philadelphia University, Philadelphia PA 19144-5497
Country: UNITED STATES
Tel: 951-2824
Tel prefix: 215
Fax: 951-2652
E-mail address: sanfordj@philau.edu
Other E-mails: jsan267@yahoo.com
Title of the Paper: Classification Data Mining with Hybrid Fuzzy Logic Aggrigation
Authors as they appear in the Paper: John F. Sanford, Les M. Sztandera
Email addresses of all the authors: sanfordj@philau.edu, sztanderal@phhilau.edu
Number of paper pages: 11
Abstract: Abstract - Fuzzy logic is applied to the category discrimination problem related to identification of mammary lesions as benign or malignant. Results of other similar studies are reviewed. The current analysis expands the fuzzy logic approach by using the normal distribution function as set membership functions and using a genetic algorithm to optimize performance with the training partition. The approach is applicable to problems having arbitrarily large number of parameters. Two different data sets are examined. Data is portioned into a training set and validation set and each set is segregated into benign and malignant records. Values of mean and standard deviation are initially computed from the associated attributes and are different for the benign and malignant records. In one training method the standard deviations are adjusted to minimize overall error. In a second method a bias adjusts the importance of each membership function. Defuzzification is accompli!
shed in three ways: modified averaging and OR process; comparison of multiplied fuzzy set values, and multiplied squared set values
Keywords: Fuzzy, Data-analysis, Discrimination, Statistical-Analysis, Screening, Genetic-algorithm
EXTENSION of the file: .doc
Special (Invited) Session: Applied Software Computing
Organizer of the Session: Dr. Les Sztandera
How Did you learn about congress: Fuzzy Logic data-analysis data discrimination
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