By Petra Perner
This e-book constitutes the refereed lawsuits of the fifteenth commercial convention on Advances in facts Mining, ICDM 2015, held in Hamburg, Germany, in July 2015.
The sixteen revised complete papers awarded have been rigorously reviewed and chosen from quite a few submissions. the subjects variety from theoretical features of knowledge mining to purposes of knowledge mining, resembling in multimedia information, in advertising, in drugs and agriculture, and in approach regulate, and society.
Read Online or Download Advances in Data Mining: Applications and Theoretical Aspects: 15th Industrial Conference, ICDM 2015, Hamburg, Germany, July 11-24, 2015, Proceedings PDF
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Extra resources for Advances in Data Mining: Applications and Theoretical Aspects: 15th Industrial Conference, ICDM 2015, Hamburg, Germany, July 11-24, 2015, Proceedings
Stat. Soc. Appl. Stat. Part 3 62, 309–369 (2013) 14. : The Elements of Statistical Learning. Springer, New York (2009) 15. : Ward’s hierarchical agglomerative clustering method: which algorithms implement ward’s criterion? J. Classif. 31, 274–295 (2014) 16. : Mining association rules between sets of items in large databases. In: SIGMOD 1993 Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207–216 (1993) 17. Turkish Statistical Institute. tr 18. Real Estate Index.
We represented the two decision trees in a user-friendly graphical form. Thus, we had, for each of the two selected clusters, a centroid representation in a tabular format, a graphically represented tree and a set of text-based rules. Figure 1 shows the centroid representation of the two clusters – along with the mean and mode values for the full data set (which can be used for comparison and to detect potentially meaningful deviations). Figure 2 shows part of the tree representation and the full rule representation of cluster 5.
Table 1. Type, scale and source of variables used for the segmentation task Variable Store size Average rental Competitor Single Married Age 0–19 Age 20–39 Age 40–59 Age 60+ Low educated Middle educated High educated Factory area University area Trade area Touristic area Car park Bus service Type Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric Numeric Binary Binary Binary Binary Binary Binary Scale Square meter Turkish Currency Number Percentage Percentage Percentage Percentage Percentage Percentage Percentage Percentage Percentage 0–1 0–1 0–1 0–1 0–1 0–1 Source Retailer’s web site Real estate companies Google Maps Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Turkish Statistical Institute Google Maps Google Maps Google Maps Google Maps Retailer’s web site Retailer’s web site Characteristics of store area Store size 20 Frequency of No 15 Frequency 10 0 100-200 200-300 300-400 400-500 500-600 600-700 700-800 800-900 900-1000 1000-1100 1100-1200 1200-1300 1300-1400 1400-1500 1500+ 5 m2 (A) 70 60 50 40 30 20 10 0 Frequency of Yes (B) Fig.