Patent Document ID: 7882050
Application ID: 11385738
Patent Flag: 1

Claim One:
1. A data division apparatus which divides multi-dimensional data including a plurality of data pieces, comprising: a data input unit which inputs the multi-dimensional data; a division plane candidate creator which creates a plurality of division plane candidates for dividing the multi-dimensional data; a data provisional division unit which provisionally divides the multi-dimensional data by using the division plane candidates to generate clusters from each of the division plane candidates, the clusters each including one or more data piece; a model generator which generates models representing the clusters, per each of the division plane candidates; an evaluation value calculator which calculates evaluation values for evaluating the division plane candidates, on the basis of the models generated associated with the division plane candidates and the multi-dimensional data; a division candidate selector which compares evaluation values respectively corresponding to the division plane candidates and selects a division plane candidate having a highest evaluation value; and a data division unit which divides the multi-dimensional data by using the selected division plane candidate, wherein the evaluation value calculator calculates errors of the generated models on the basis of the generated models and clusters respectively corresponding to the generated models, divides an error of a model corresponding to the multi-dimensional data by the number of data pieces contained in the multi-dimensional data, calculates model evaluation values respectively of the models on the basis of the calculated errors of the models, a result value of the dividing, and numbers of data pieces respectively contained in the clusters, calculates the evaluation value based on the model evaluation values of the models, wherein the evaluation value calculator calculates the model evaluation value of each of the models by subtracting a product of the dividing result value and the number of data pieces contained in each of the clusters and a parameter value from the calculated error of each of the models.