About: Rules extraction system family

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The rules extraction system (RULES) family is a family of inductive learning that includes several covering algorithms. This family is used to build a predictive model based on given observation. It works based on the concept of separate-and-conquer to directly induce rules from a given training set and build its knowledge repository. Algorithms under RULES family are usually available in data mining tools, such as KEEL and WEKA, known for knowledge extraction and decision making.

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  • The rules extraction system (RULES) family is a family of inductive learning that includes several covering algorithms. This family is used to build a predictive model based on given observation. It works based on the concept of separate-and-conquer to directly induce rules from a given training set and build its knowledge repository. Algorithms under RULES family are usually available in data mining tools, such as KEEL and WEKA, known for knowledge extraction and decision making. (en)
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  • The rules extraction system (RULES) family is a family of inductive learning that includes several covering algorithms. This family is used to build a predictive model based on given observation. It works based on the concept of separate-and-conquer to directly induce rules from a given training set and build its knowledge repository. Algorithms under RULES family are usually available in data mining tools, such as KEEL and WEKA, known for knowledge extraction and decision making. (en)
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  • Rules extraction system family (en)
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