Data Mining And Knowledge Discovery

1661 Words Apr 22nd, 2016 7 Pages
Data miming
Data mining or Knowledge Discovery in Databases (KDD) is discovering patterns from large data groups through methods of artificial intelligence, machine learning ,statistics, and database systems. The aim of data mining process is to extract information from a data group and switch it to an ideal format for future . The data mining process comprise of database and data management aspects, data preprocessing, inference, complexity of discovered structures, and updating.
The Data mining have many techniques for extracting dataset like Clustering, Classification, Regression, and Association Rule Learning. The clustering technique is the task of discovering structures in homogeneous data to be in one group, there the classification technique is the task of generalizing structure to applied it in for new data. And Regression is the effort of finding a task which model the data with less error. Also, the Association Rule Learning is search for a relationships between variables.
Security in Data Mining
Data mining has standout to provide tools and applications for the users to identify the vulnerabilities and help them to gain a covering mechanism against information systems threats. There are various techniques of data mining in the information security like example intrusion detection , prevention systems and Network intrusion detection. It is analysis the threat to identify bad actions that effect the integrity, confidentiality, and availability of…

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