A statistical approach to case based reasoning, with application to breast cancer data

Authors:
J. Dippon;P. Fritz;M. Kohler
Affiliations:
Mathematisches Insitut A, Universität Stuttgart, 70511 Stuttgart, Germany;Pathologisches Institut, Robert--Bosch--Krankenhaus, 70376 Stuttgart, Germany;Mathematisches Insitut A, Universität Stuttgart, 70511 Stuttgart, Germany
Venue:
Computational Statistics & Data Analysis
Year:
2002

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Abstract

Given a large set of problems and their individual solutions case based reasoning seeks to solve a new problem by referring to the solution of that problem which is "most similar" to the new problem. Crucial in case based reasoning is the decision which problem "most closely" matches a given new problem. A new method is proposed for deciding this question. The basic idea is to define a family of distance functions and to use these distance functions as parameters of local averaging regression estimates of the final result. Then that distance function is chosen for which the resulting estimate is optimal with respect to a certain error measure used in regression estimation. The method is illustrated by simulations and applied to breast cancer data.