A NEURO FUZZY EXPERT SYSTEM FOR HEART DISEASE DIAGNOSIS

Heart disease in India is one of the major causes of death. This disease is common not only in old and middle aged people but also in young people. It is caused due to improper diet habits. The proposed system finds a solution to diagnose the disease using some of the evolutionary computing techniques like genetic algorithm, fuzzy rule based learning and neural networks. The neuro fuzzy classification of the disease with the help of genetic algorithms for feature selection is the frame work of the proposed system.

[1]  金田 重郎,et al.  C4.5: Programs for Machine Learning (書評) , 1995 .

[2]  Tzung-Pei Hong,et al.  Induction of fuzzy rules and membership functions from training examples , 1996, Fuzzy Sets Syst..

[3]  Shyi-Ming Chen,et al.  A NEW METHOD TO CONSTRUCT MEMBERSHIP FUNCTIONS AND GENERATE WEIGHTED FUZZY RULES FROM TRAINING INSTANCES , 2005, Cybern. Syst..

[4]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[5]  Shyi-Ming Chen,et al.  Generating Weighted Fuzzy Rules from Training Instances Using Genetic Algorithms to Handle the Iris Data Classification Problem , 2006, J. Inf. Sci. Eng..

[6]  Zhaohui Tang,et al.  Data Mining with SQL Server 2005 , 2005 .

[7]  Ron Kohavi,et al.  Feature Selection for Knowledge Discovery and Data Mining , 1998 .

[8]  Shyi-Ming Chen,et al.  AUTOMATICALLY CONSTRUCTING MEMBERSHIP FUNCTIONS AND GENERATING FUZZY RULES USING GENETIC ALGORITHMS , 2002 .

[9]  Sudipto Guha,et al.  ROCK: a robust clustering algorithm for categorical attributes , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[10]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[11]  Shyi-Ming Chen,et al.  A new method for constructing membership functions and fuzzy rules from training examples , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[12]  Shyi-Ming Chen,et al.  Generating Weighted Fuzzy Rules for Handling Classification Problems , 2005, Int. J. Electron. Bus. Manag..

[13]  Paulo Cortez,et al.  Data Mining with , 2005 .

[14]  Shyi-Ming Chen,et al.  A New Approach for Handling the Iris Data Classification Problem , 2005 .

[15]  Kemal Polat,et al.  Diagnosis of heart disease using artificial immune recognition system and fuzzy weighted pre-processing , 2006, Pattern Recognit..

[16]  Huan Liu,et al.  Consistency Based Feature Selection , 2000, PAKDD.

[17]  Shyi-Ming Chen,et al.  A new method to construct membership functions and generate fuzzy rules from training instances , 2005 .

[18]  Shyi-Ming Chen,et al.  A new method to deal with fuzzy classification problems by tuning membership functions for fuzzy classification systems , 2005 .

[19]  Swapnil Patil,et al.  Computer Science & Engineering: An International Journal (CSEIJ) , 2012 .

[20]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[21]  Tzung-Pei Hong,et al.  Finding relevant attributes and membership functions , 1999, Fuzzy Sets Syst..

[22]  Shyi-Ming Chen,et al.  A NEW METHOD FOR CONSTRUCTING FUZZY DECISION TREES AND GENERATING FUZZY CLASSIFICATION RULES FROM TRAINING EXAMPLES , 2000, Cybern. Syst..

[23]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[24]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[25]  Shyi-Ming Chen,et al.  Generating Weighted Fuzzy Rules from Training Data for Dealing with the Iris Data Classification Problem , 2006 .

[26]  Tzung-Pei Hong,et al.  Effect of merging order on performance of fuzzy induction , 1999, Intell. Data Anal..

[27]  Johannes Gehrke,et al.  CACTUS—clustering categorical data using summaries , 1999, KDD '99.

[28]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .