Unsupervised Clustering Categorical Data Using Evolutionary Optimization Techniques
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Beschrijving
Bol
Data Mining (DM) [1] is defined as the extraction of knowledge from data. Several existing tools in data mining are available to forecast the trends in the data. In addition, Data mining can be used to identify and remove the irrelevant information. Apart from this, it enables us to derive knowledge, through which it become to make decisions that are used as a proactive measure in this process analysis. The traditional methods in knowledge extraction process that are under implementation at present are time consuming methods. Whereas the data mining has resolved this issue by overcoming the time consumption.
Beschrijving
(1)
Data Mining (DM) [1] is defined as the extraction of knowledge from data. Several existing tools in data mining are available to forecast the trends in the data. In addition, Data mining can be used to identify and remove the irrelevant information. Apart from this, it enables us to derive knowledge, through which it become to make decisions that are used as a proactive measure in this process analysis. The traditional methods in knowledge extraction process that are under implementation at present are time consuming methods. Whereas the data mining has resolved this issue by overcoming the time consumption.
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