Optimization of Decision Rules in Fuzzy Classification

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@Article{Arora:2012:IJCA,

• title = "Optimization of Decision Rules in Fuzzy Classification",
• author = "Renuka Arora and Sudesh Kumar",
• journal = "International Journal of Computer Applications",
• year = "2012",
• volume = "51",
• number = "3",
• pages = "13--17",
• month = aug,
• keywords = "genetic algorithms, genetic programming",
• ISSN = "09758887",
• bibsource = "OAI-PMH server at www.doaj.org",
• language = "eng",
• oai = "oai:doaj-articles:2c58ebd9b3af7344384924c400738db2",
• URL = "http://research.ijcaonline.org/volume51/number3/pxc3880505.pdf",
• DOI = "doi:10.5120/8021-0505",
• publisher = "Foundation of Computer Science (FCS)",
• size = "5 pages",
• abstract = "There are various advances in data collection that can intelligently and automatically analyse and mine knowledge from large amounts of data. World Wide Web as a global information system has flooded us with a tremendous amount of data and information Discovery of knowledge and decision-making directly from such huge volumes of data contents is a real challenge. The Knowledge Discovery in Databases (KDD) is the process of extracting the knowledge from huge data collection. Data mining is a step of KDD in which patterns or models are extracted from data by using some automated techniques. Discovering knowledge in the form of classification rules is one of the most important tasks of data mining. Discovery of comprehensible, concise and effective rules helps us to make right decisions. Therefore, several Machine Learning techniques are applied for discovery of classification rules. Recently there have been several applications of genetic algorithms for effective rules with high predictive accuracy.",
• notes = "Balloon, Poker",

}

Genetic Programming entries for Renuka Arora Sudesh Kumar

Citations