An Optimistic Data Mining Approach for Handling Large Data Set using Data Partitioning Techniques

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
The use of the Internet for various purposes leads to collection of large volume of data. The knowledge contents of large data can be utilized to improve decision-making process of an organization. The knowledge discovery on this high volume data becomes very slow, as it has to be done serially on currently available terabyte plus data sets. In some cases, mining of large data set may become impossible due to limitations of processor and memory. The proposed algorithm is based on the authors' findings which state that increasing size of training data does not considerably increase classification accuracy of a classifier.

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