Data Mining is considered as an interdisciplinary field. It includes a set of various disciplines such as statistics, database systems, machine learning, visualization, and information sciences. Classification of the data mining system helps users to understand the system and match their requirements with such systems.
Data mining discovers patterns and extracts useful information from large datasets. Organizations need to analyze and interpret data using data mining systems as data grows rapidly. With an exponential increase in data, active data analysis is necessary to make sense of it all.
Data mining (DM) systems can be classified based on various factors.
A database mining system can be classified based on ‘type of data’ or ‘use of data’ model or ‘application of data.’
For Example: Relational Database, Transactional Database, Multimedia Database, Textual Data, World Wide Web (WWW) and etc,
We can classify a data mining system according to the kind of knowledge mined. It means the data mining system is classified based on functionalities such as
We can classify a data mining system according to the kind of techniques used. We can describe these techniques according to the degree of user interaction involved or the methods of analysis employed.
Data Mining systems use various techniques, including Statistics, Machine Learning, Database Systems, Information retrieval, Visualization, and pattern recognition.
We can classify a data mining system according to the applications adapted. These applications are as follows