- Trending Categories
Data Structure
Networking
RDBMS
Operating System
Java
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
What is the classification of data mining systems?
Data mining refers to extracting or mining knowledge from large amounts of data. Data mining is generally used in places where a huge amount of data is saved and processed.
Data mining is an interdisciplinary field, the assemblage of a set of disciplines, such as database systems, statistics, machine learning, visualization, and data science. It is depending on the data mining approach used, techniques from other disciplines may be applied, such as neural networks, fuzzy and/or rough set theory, knowledge representation, inductive logic programming, or high-performance computing.
It is established on the types of data to be mined or on the given data mining application, the data mining system can also integrate methods from spatial data analysis, data retrieval, pattern identification, image analysis, signal processing, computer graphics, network technology, economics, business, bioinformatics, or psychology.
The classification of data mining is as follows −
Classification according to the kinds of databases mined − A data mining system can be classified according to the kinds of databases mined. Database systems can be classified according to various criteria (including data models, or the types of data or applications contained), each of which can need its data mining technique.
For example, if classifying according to data models, it can have a relational, transactional, object-relational, or data warehouse mining system. If classifying according to the special types of data handling, we may have a spatial, time-series, text, stream data, multimedia data mining system, or a World Wide Web mining system.
Classification according to the kinds of knowledge mined − Data mining systems can be categorized according to the kinds of knowledge they mine. It is based on data mining functionalities, including characterization, discrimination, association, and correlation analysis, classification, prediction, clustering, outlier analysis, and evolution analysis. A data mining system generally supports multiple and integrated data mining functionalities.
Classification according to the kinds of techniques utilized − Data mining systems can be categorized according to the fundamental data mining techniques employed. These techniques can be described according to the degree of user interaction involved in autonomous systems, interactive exploratory systems, query-driven systems, or the methods of data analysis employed.
Classification according to the applications adapted − Data mining systems can also be categorized according to the applications they adapt. For instance, data mining systems can be tailored categorically for finance, telecommunications, DNA, stock markets, e-mail, etc. There are multiple applications often needed the integration of application-specific methods.
- Related Articles
- What are the data Mining methods for Recommender Systems?
- What is the difference between feed-forward and feedback systems in data mining?
- What are the various Issues regarding Classification and Prediction in data mining?
- Signals and Systems: Classification of Systems
- What is Data Classification?
- What is the architecture of data mining?
- What is the History of Data Mining?
- What is the task of Data Mining?
- What is Data Mining?
- What is the Temporal Data Mining?
- What is the techniques of statistical data mining?
- What is the theoretical foundations of Data Mining?
- What is the difference between Text Mining and Data Mining?
- Signals and Systems – Classification of Signals
- What is Data Mining Metrics?
