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Artículo
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
(Elsevier, 2018)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. However, this task is becoming a challenge because the processing power of most existing techniques ...
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An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark
(Springer, 2016)
K-Means and Bisecting K-Means clustering algorithms need the optimal number into which the dataset may be divided. Spark implementations of these algorithms include a method that is used to calculate this number. Unfortunately, ...