By Jeff Kent
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Extra info for Visual and Spatial Analysis - Advances in Data Mining, Reasoning, and Problem Solving
Here the sizes of circles indicate the relative number of methods currently available (part a) and the relative number of methods desired (part b). It is obvious from this figure that new methods dealing with full-solution algorithms for discovery tasks are in short supply. A A Discovery @ @ 0 Reasoning @ @I@ @ Discovery Reasoning @ @D @ @ @ @ Heurbtie algorithm Fulkolution algorithm e illustration b Informal Algorithm Henristic algorithm Full-solution algorithm (a) Available methods Illustration ,' Informal Algorithm b (b) Desired new methods Figure 7.
Above. The model (b) for the analyst must be complex enough to cover a wide range of possible decision alternatives. ) produced a single decision alternative - to shut down the pump/well d. A model of type (b) for the analyst might include many other alternatives to be explored: 1. Restrict the access of new people to the city, 2. Restrict the contact between people in the city limit, 3, Restrict the consumption of certain foods, 4. Use certain medications, 5. Restrict the contact of the population with certain animals, 6.
These objects may be suspected of being related to the high death toll. We call this structured information for the DM. Thus, the DM model will grow like a tree (see Figure 10). The rectangles show relations to be investigated. After providing such structural information, an analyst can investigate relations between death toll and each of the components: pumps, distribution routes, methods of water treatment and type of population. Currently this process is done by spatial data mining techniques (see Chapter 12 on SPIN system in this book).