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Pattern mining has been widely used to uncover interesting patterns from data. However, one of its main problems is that it produces too many patterns and many of them are redundant. To reduce the number of redundant patterns and retain overlapping ones, delta-closed pattern pruning was introduced, yet it can only prune subpatterns if they are covered by superpatterns. Such unduly superpatterns need...
The curse of dimensionality refers to the problem that one faces when analyzing datasets with thousands or hundreds of thousands of attributes. This problem is usually tackled by different feature selection methods which have been shown to effectively reduce computation time, improve prediction performance, and facilitate better understanding of datasets in various application areas. These methods...
In order to determine how data mining techniques (DMT) and their applications have developed, during the past decade, this paper reviews data mining techniques and their applications and development, through a survey of literature and the classification of articles, from 2000 to 2011. Keyword indices and article abstracts were used to identify 216 articles concerning DMT applications, from 159 academic...
In many Buck converter applications, soft start feature with pre-biased output voltage condition is often necessary to avoid undesirable effects such as in-rush start current, possible inductor saturation, and output voltage overshoot during power-up period. However, in a synchronous Buck converter configuration, such starting condition would lead to output voltage temporary dipping during power-up,...
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