slides_G_ii.md

Geographic Data Science

Non-spatial clustering [Dani Arribas-Bel](http://darribas.org)

Non-spatial clustering

Split a dataset into groups of observations that are similar within the group and dissimilar between groups, based on a series of attributes

Machine learning

The computer *learns* some of the properties of the dataset without the human specifying them

Unsupervised

There is no a-priori structure imposed on the classification $\rightarrow$ before the analysis, no observations is in a category

Intuition

K-means

• Most popular clustering algorithm
• Good but not perfect
• Watch video for int

More clustering...

• Hierarchical clustering
• Agglomerative clustering
• Spectral clustering
• Neural networks (e.g. Self-Organizing Maps)
• DBSCAN
• ...

Different properties, different best usecases

See interesting comparison table

Geodemographic analysis

Geodemographic analysis

1970’s, Richard Webber Identify similar neighborhoods $\rightarrow$ Target urban deprivation funding Public Sector (policy) $\rightarrow$ Private sector (marketing and business intelligence)

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Source

A course on Geographic Data Science by Dani Arribas-Bel is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.