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Accuracy and efficiency of clustering algorithms depend greatly on the input data. Thus, removing unimportant features from the dataset can help us form better clusters in lesser time. These unimportant features may be those that are redundant, or affected by noise, etc. We also need to consider the fact that the features we finally choose, should represent the original dataset in the best possible...
The closeness of the 2000 presidential election, especially in the state of Florida, has drawn attention to the importance of voting anomalies caused by ballot design, voting technology, and voter errors. In this paper we focus on a particular type of voter error: casting multiple votes for president on a single ballot. Ballots cast in this way are said to contain presidential overvotes, and we examine...
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