Data mining is a genome in which useful patterns or trends can be found for large amounts of computerized data. Data mining is an interdisciplinary area of ​​computer science that explores patterns of large-scale data systems. Data mining is a genome in which useful patterns or trends can be found for large amounts of computerized data. Data mining is an interdisciplinary area of ​​computer science that explores patterns of large data sets using artificial intelligence, machine learning, statistics and database systems. The peer review refers to the pre-selection of submitted manuscripts and funding requests during the work carried out. This process encourages authors to respect norms of their discipline and reduction of irrelevant findings, unjustified claims, unacceptable interpretations and personal opinions.
Data mining is the process of discovering patterns in large data sets using the intersection of machine learning, statistics and database systems. Data mining is an interdisciplinary sub-domain of IT and statistics with the overall objective of extracting information (intelligent methods) for later use of a dataset and transforming information. Data mining is the process of "knowledge discovery in databases", or KDD. In addition to the raw analysis stage, it also includes aspects of database and data management, data preprocessing, modeling and reference considerations, metrics of interest, considerations of complexity, post-processing of structures, online viewing and updating. Data mining can be unintentionally misused and can then produce results that seem significant; But this is not a new sample of data and are of little use. Often, many of the hypotheses investigating from these results and not performing an appropriate statistical hypothesis test. data mining can be unintentionally be misused and can then produce results that seem meaningful