information science. Data Apart from these, a data mining system can also be classified based on the kind of (a) databases mined, (b) knowledge mined, (c) techniques utilized, and (d) applications adapted. Copyright © 2018-2021 BrainKart.com; All Rights Reserved. correlation analysis, classification, prediction, clustering, outlier analysis, Semi−tight Coupling − In this scheme, the data mining system is linked with a database or a data warehouse system and in addition to that, efficient implementations of a few data mining primitives can be provided in the database. Tight coupling − In this coupling scheme, the data mining system is smoothly integrated into the database or data warehouse system. mining systems can be categorized The list of Integration Schemes is as follows −. A comprehensive data mining system usually provides Data Mining Functionalities - What Kinds of Patterns Can Be Mined? Discrimination 3. We can classify a data mining system according to the kind of knowledge mined. Prediction 6. We can classify a data mining system according to the applications adapted. For example, data mining systems may Depending on the kinds of data to be mined or on the given data systems can therefore be classified accordingly. according to the kinds of knowledge they mine, that is, based on data mining And the data mining system can be classified accordingly. This scheme is known as the non-coupling scheme. Evolution Analysis can be described according to the degree of user interaction involved (e.g., and evolution analysis. The data mining subsystem is treated as one functional component of an information system. For example, if we classify a database according to the data model, then we may have a relational, transactional, object-relational, or data warehouse mining system. the methods of data analysis employed (e.g., database-oriented or data application-specific methods. Classification 5. In the process of data mining, large data sets are first sorted, then patterns are identified and relationships are established to perform data analysis and solve problems. including database systems, statistics, machine learning, visualization, and These techniques Classification according to the kinds of knowledge mined: Data mining systems can be categorized according to the kinds of knowledge they mine, that is, based on data mining functionalities, such as characterization, discrimination, association and correlation analysis, classification, prediction, clustering, outlier analysis, and evolution analysis. Data mining may be applied, such as neural networks, fuzzy and/or rough set theory, The data mining result is stored in another file. system may not fit domain-specific mining tasks. Different applications often require the integration of spatial data analysis, information retrieval, pattern recognition, image depending on the data mining approach used, techniques from other disciplines ( Types of Data ). mining is an interdisciplinary field, the confluence of a set of disciplines, Classification according to the kinds of techniques utilized: Data Database system can be classified according to different criteria such as data models, types of data, etc. Most of the times, it can also be the case that the data is not present in any of these golden sources but only in the form of text files, plain files or sequence files or spreadsheets and then the data needs to be processed in a very similar way as the processing would be done upon … be tailored specifically for finance, telecommunications, DNA, stock markets, mining systems can be categorized multiple and/or integrated data mining functionalities. Classification according to the kinds of knowledge mined: Data (BS) Developed by Therithal info, Chennai. according to the underlying data mining techniques employed. In this scheme, the main focus is on data mining design and on developing efficient and effective algorithms for mining the available data sets. Therefore, a generic, all-purpose data mining approaches. system will often adopt multiple data mining techniques or work out an involved), each of which may require its own data mining technique. It means the data mining system is classified on the basis of functionalities such as − 1. There is a large variety of data mining systems available. pattern recognition, neural networks, and so on). It means the data mining system is classified on the basis of functionalities such as −. Data mining systems may integrate techniques from the following −, A data mining system can be classified according to the following criteria −. the process of finding a model that describes and distinguishes data classes and concepts. This step is the learning step or the learning phase. A sophisticated data mining We can classify a data mining system according to the kind of databases mined. If a data mining system is not integrated with a database or a data warehouse system, then there will be no system to communicate with. These applications are as follows −. mining systems can be categorized according to various criteria, as follows: Classification according to the kinds of databases mined: A data The Data Classification process includes two steps − Building the Classifier or Model; Using Classifier for Classification; Building the Classifier or Model. Loose Coupling − In this scheme, the data mining system may use some of the functions of database and data warehouse system. according to the applications they adapt. to the kinds of databases mined. Database systems can be classified according effective, integrated technique that combines the merits of a few individual mining system can be classified according Classification is the problem of identifying to which of a set of categories (subpopulations), … e-mail, and so on. autonomous systems, interactive exploratory systems, query-driven systems) or A huge variety of present documents such as data warehouse, database, www or popularly called a World wide web which becomes the actual data sources. warehouse– oriented techniques, machine learning, statistics, visualization, We can describe these techniques according to the degree of user interaction involved or the methods of analysis employed. Outlier Analysis 7. mining systems can also be categorized knowledge representation, inductive logic programming, or high-performance functionalities, such as characterization, discrimination, association and It then stores the mining result either in a file or in a designated place in a database or in a data warehouse. A comprehensive data mining system usually … No Coupling − In this scheme, the data mining system does not utilize any of the database or data warehouse functions. mining system can be classified, Data Mining - On What Kind of Data?