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Miscellaneous Distributed Weka capabilities

Mark Hall shows how to compute a correlation matrix in Distributed Weka for input to Principal Component Analysis, and a parallel version of k-means.

There are other useful KnowledgeFlow templates for Distributed Weka. One computes a correlation matrix for input to Principal Component Analysis; another runs a parallel version of the k-means clustering algorithm. To process large datasets you need to run Distributed Weka on a cluster. The Apache Spark website contains information on how to set up a cluster; this blog post explains how to run a Spark cluster on a single machine using separate Java processes that communicate as though they were running on different machines – which is different from the “local mode” we’ve been using, where the entirety of Spark runs in a single Java process.

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Advanced Data Mining with Weka

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