Geographic Data Science

Non-spatial clustering
Dani Arribas-Bel

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 → before the analysis, no observations is in a category

Intuition

Clustering

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 → Target urban deprivation funding
  • Public Sector (policy) → Private sector (marketing and business intelligence)
 Predictive Postcode

Source

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