Data Mining
Performing clustering technique of data mining using Waikato Environment for Knowledge Analysis Version 3.6.5.
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Data mining can be considered a relatively recently developed methodology and technology, coming into prominence only in 1994. It aims to identify valid, novel, potentially useful, and understandable correlations and patterns in data by combing through copious data sets to sniff out patterns that are too subtle or complex for humans to detect. Data mining can be defined as the process of finding previously unknown patterns and trends in databases and using that information to build predictive models. It is the process of data selection and exploration and building models using vast data stores...
Data mining can be considered a relatively recently developed methodology and technology, coming into prominence only in 1994. It aims to identify valid, novel, potentially useful, and understandable correlations and patterns in data by combing through copious data sets to sniff out patterns that are too subtle or complex for humans to detect. Data mining can be defined as the process of finding previously unknown patterns and trends in databases and using that information to build predictive models. It is the process of data selection and exploration and building models using vast data stores to uncover previously unknown patterns. Data mining can improve decisionmaking by discovering patterns and trends in large amounts of complex data. Data Mining is the discovery of knowledge of analyzing enormous set of data; by extracting the meaning of the data and then predicting the future trends and also helps companies to take sound decisions, based on knowledge and information. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified.
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