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In this digital ITEMS module, Nikole Gregg and Dr. Brian Leventhal discuss strategies to ensure data visualizations achieve graphical excellence. Data visualizations are commonly used by measurement professionals to communicate results to examinees, the public, educators, and other stakeholders. To do so effectively, it is important that these visualizations communicate data efficiently and accurately...
Grid computing provides integrated high-end compute resources across administrative domains. More and more grid infrastructures are being used for mission-critical scientific and engineering applications. Ensuring security and safety of grid environment is a key challenge faced by grid community. First step towards grid security is to be aware of vulnerabilities and weaknesses in the entire grid....
This paper illustrates the use of data mining and data visualization techniques to mine multidimensional database for the selected data of forest cover type consisting of 63,377 records each with 54 attributes. Using SAS?? enterprise miner, The paper performs analysis of such data mining functionalities as decision tree, regression analysis, neural network, clustering analysis, and association analysis...
Complexity of data analysis in data mining often makes results difficult to interpret. This problem could be solved using various approaches. Principal component analysis (PCA) and disjoint cluster analysis (DCA) are methods used for data reduction and summarization. In this paper, PCA and DCA were applied on dataset example containing information about students' courses and time necessary to pass...
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