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labs/multivariate-analysis/04-classification-and-clustering.Rmd

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Classification and clustering is an enormous topic area with numerous different methods available, many of them now falling under the rubric of machine-learning.
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OK... on to [statistical modelling](05-statistical-models.md).
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OK... on to [statistical modelling](05-assignment-multivariate-analysis.md).

labs/multivariate-analysis/04-classification-and-clustering.md

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It's good to see that there are clear similarities between this output and the k-means one (at least there were first time I ran the analysis!)
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As with k-means, there are more details around all of this. Different approaches to calculating distances can be chosen (see `?dist`) and various options for the exact algorith for merging clusters are available by setting the `method` option in the `hclust` function. The function help is the place to look for more information. Other clustering methods are also available. A recently popular one has been the DBSCAN family of methods([here is an R package](https://github.com/mhahsler/dbscan)).
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As with k-means, there are more details around all of this. Different approaches to calculating distances can be chosen (see `?dist`) and various options for the exact algorith for merging clusters are available by setting the `method` option in the `hclust` function. The function help is the place to look for more information. Other clustering methods are also available. A recently popular one has been the DBSCAN family of methods([here is an R package](https://github.com/mhahsler/dbscan)).
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Once clusters have been assigned, we can do further analysis comparing characteristics of different clusters. For example
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Classification and clustering is an enormous topic area with numerous different methods available, many of them now falling under the rubric of machine-learning.
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OK... on to [the assignment](05-statistical-models.md).
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OK... on to [the assignment](05-assignment-multivariate-analysis.md).

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