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  2. Choropleth map - Wikipedia

    en.wikipedia.org/wiki/Choropleth_map

    The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin, depicting the availability of basic education in France by department. [4] More "cartes teintées" ("tinted maps") were soon produced in France to visualize other "moral statistics" on education, disease, crime, and living conditions.

  3. Group concept mapping - Wikipedia

    en.wikipedia.org/wiki/Group_concept_mapping

    The resulting maps display the individual statements in two-dimensional space with more similar statements located closer to each other, and grouped into clusters that partition the space on the map. The Concept System software also creates other maps that show the statements in each cluster rated on one or more scales, and absolute or relative ...

  4. Cluster diagram - Wikipedia

    en.wikipedia.org/wiki/Cluster_diagram

    A cluster in general is a group or bunch of several discrete items that are close to each other. The cluster diagram figures a cluster, such as a network diagram figures a network, a flow diagram a process or movement of objects, and a tree diagram an abstract tree. But all these diagrams can be considered interconnected: A network diagram can ...

  5. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).

  6. Self-organizing map - Wikipedia

    en.wikipedia.org/wiki/Self-organizing_map

    Self-organizing maps, like most artificial neural networks, operate in two modes: training and mapping. First, training uses an input data set (the "input space") to generate a lower-dimensional representation of the input data (the "map space"). Second, mapping classifies additional input data using the generated map.

  7. Nearest-neighbor chain algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest-neighbor_chain...

    The cluster distances for which the nearest-neighbor chain algorithm works are called reducible and are characterized by a simple inequality among certain cluster distances. The main idea of the algorithm is to find pairs of clusters to merge by following paths in the nearest neighbor graph of the clusters. Every such path will eventually ...