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- Data_mining abstract "Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.The term is a buzzword, and is frequently misused to mean any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) but is also generalized to any kind of computer decision support system, including artificial intelligence, machine learning, and business intelligence. In the proper use of the word, the key term is discovery,[citation needed] commonly defined as "detecting something new". Even the popular book "Data mining: Practical machine learning tools and techniques with Java" (which covers mostly machine learning material) was originally to be named just "Practical machine learning", and the term "data mining" was only added for marketing reasons. Often the more general terms "(large scale) data analysis", or "analytics" – or when referring to actual methods, artificial intelligence and machine learning – are more appropriate.The actual data mining task is the automatic or semi-automatic analysis of large 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). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting are part of the data mining step, but do belong to the overall KDD process as additional steps.The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These methods can, however, be used in creating new hypotheses to test against the larger data populations.".
- Data_mining wikiPageExternalLink chen_tkde96.pdf.
- Data_mining wikiPageExternalLink api.
- Data_mining wikiPageExternalLink www.fortewares.com.
- Data_mining wikiPageExternalLink qiware.
- Data_mining wikiPageExternalLink www.intelnics.com.
- Data_mining wikiPageExternalLink neuraldesigner.
- Data_mining wikiPageID "42253".
- Data_mining wikiPageRevisionID "605668799".
- Data_mining hasPhotoCollection Data_mining.
- Data_mining subject Category:Data_analysis.
- Data_mining subject Category:Data_mining.
- Data_mining subject Category:Formal_sciences.
- Data_mining comment "Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.".
- Data_mining label "Data mining".
- Data_mining label "Data mining".
- Data_mining label "Data mining".
- Data_mining label "Data-Mining".
- Data_mining label "Datamining".
- Data_mining label "Eksploracja danych".
- Data_mining label "Exploration de données".
- Data_mining label "Mineração de dados".
- Data_mining label "Minería de datos".
- Data_mining label "تنقيب في البيانات".
- Data_mining label "データマイニング".
- Data_mining label "数据挖掘".
- Data_mining sameAs Data_mining.
- Data_mining sameAs Data-Mining.
- Data_mining sameAs Εξόρυξη_δεδομένων.
- Data_mining sameAs Minería_de_datos.
- Data_mining sameAs Datu-meatzaritza.
- Data_mining sameAs Exploration_de_données.
- Data_mining sameAs Penggalian_data.
- Data_mining sameAs Data_mining.
- Data_mining sameAs データマイニング.
- Data_mining sameAs 데이터_마이닝.
- Data_mining sameAs Datamining.
- Data_mining sameAs Eksploracja_danych.
- Data_mining sameAs Mineração_de_dados.
- Data_mining sameAs m.0blvg.
- Data_mining sameAs Q172491.
- Data_mining sameAs Q172491.
- Data_mining wasDerivedFrom Data_mining?oldid=605668799.
- Data_mining isPrimaryTopicOf Data_mining.