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I propose some functions that extend capability for optimisation of markov chain modelling using clustering. These are all extensions of existing functions that work with k-means clustering in the clickstream package.
Added a parallelized version of getConsensusClusters, and added function getParallelClusterSets (which performs the discreet function of clustering a clickstream, fitting markov chains to each cluster, and returning a list of the cluster-markovchain pair). Depends on the parallel() library.
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I propose some functions that extend capability for optimisation of markov chain modelling using clustering. These are all extensions of existing functions that work with k-means clustering in the clickstream package.