This indicator contains the result of the cluster analysis performed to classify the EU regions with respect to their potential for the KE, and their economic and labor market conditions, population and migration dynamics. Data were processed with SPSS.
Theme(s): Labour Market - Education
| Spatial Extent | Nomenclature | ||
|---|---|---|---|
| name | version | level | |
| EU28 | NUTS | 2013 | 2 |
The cluster analysis is a data classification methodology used to categorise n objects (in this case the European regions) into k (k>1) groups, called clusters, by using p (p>0) clustering variables. Within each cluster, entities are therefore "similar".
This classification has been obtained by running a K-means algorithm: given a set of observations (x1, x2, …, xn), where each observation is a p-dimensional real vector, K-means clustering aims to partition the n observations into fixed K (≤ n) sets S = {S1, S2, …, Sk} so as to minimise the within-cluster sum of squares (WCSS) (sum of distance functions of each point in the cluster to the K center).
None!
| Name | Description |
|---|---|
| 1 | Highly competitive and KE-based economy |
| 2 | Competitive and KE-related economy |
| 3 | Less competitive with potential in KE economy |
| 4 | Less competitive economy with low incidence of KE |