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The actual data mining task is the semi-automatic or automatic analysis of massive quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining, sequential pattern mining).
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using some measures of interestingness. [1]
The book: Han, Kamber and Pei, "Data Mining: Concepts and Techniques" (3rd ed., Morgan Kaufmann, 2011) has been popularly used as a textbook worldwide. He was the 2009 winner of the McDowell Award , the highest technical award made by IEEE .
Metabolomics is a very data heavy subject, and often involves sifting through massive amounts of irrelevant data before finding any conclusions. Data mining has allowed this relatively new field of medical research to grow considerably within the last decade, and will likely be the method of which new research is found within the subject. [28]
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Vipin Kumar Tripathi (alternately known as VK Tripathi; born 11 March 1948) is an Indian plasma physicist, activist, and a former Physics professor of the IIT Delhi. Life and career [ edit ]
Relational data mining is the data mining technique for relational databases. [1] Unlike traditional data mining algorithms, which look for patterns in a single table (propositional patterns), relational data mining algorithms look for patterns among multiple tables (relational patterns). For most types of propositional patterns, there are ...
Data Stream Mining (also known as stream learning) is the process of extracting knowledge structures from continuous, rapid data records. A data stream is an ordered sequence of instances that in many applications of data stream mining can be read only once or a small number of times using limited computing and storage capabilities.