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Search of optimal size of data sample for the problem of diabetes treatment monitoring


  The methods of the optimal sample size selection The nucleus of data sample is the result of appropriate reduction of the number and composition of the rows and columns of data samples [4]. Nucleus self-organization is carried out by means of two-dimensional optimization on the plane of two determined coordinates - number of rows and number of columns, unlike models’ self-organization properties. In this paper combinatorial GMDH algorithm with model selection after-determination by criterion of error bias is used for data sample nucleus search. The problem of two-dimensional exhaustive search is too large for practical application. It is replaced by a one-dimensional problem solution for enumeration of data samples which contain an equal number of rows and columns (square sampling). Combinatorial GMDH algorithm is used for a nucleus search on a square data sample [5]. Tabl. 1. Input data sample of home monitoring. T ab. 1. Dane wejściowe z pomiarów w domu Data x22k+1 x6k X12k X17k X22k i6k i12k i17k i22k 17.08.1993 6,8 10,5 10,6 5,5 7 20 12 14 12 18.08.1993 9,8 13,5 24,6 4,4 13,6 20 12 14 12 19.08.1993 15,3 14,9 16,4 5,8 13,65 20 10 14 12 20.08.1993 10,2 22,5 11 ,4 6,1 13,7 20 12 14 12 21.08.1993 9,6 10 18,5 18,1 19,1 20 12 12 12 22.08.1993 16,7 17,2 14 5,8 6,4 19 12 12 12 23.08.1993 7,2 16,3 8,5 7,9 11 ,3 19 11 14 12 24.08.1993 10,9 15,2 11 ,5 8 6,8 19 9 12 12 25.08.1993 13 14 21,7 24,4 9,8 19 11 14 12 26.08.1993 20,6 21,1 10,4 11 15,3 17 11 14 12 27.08.1993 14,4 14,2 24,7 20,7 10,2 19 11 14 12 28.08.1993 20 14,3 19,6 16 9,6 18 11 14 12 29.08.1993 12,1 26,9 28,1 20,9 16,7 18 11 13 12 30.08.1993 14,9 26,9 24,5 16,5 7,2 18 11 13 12 31.08.1993 23,6 16,5 16,8 19,6 10,9 18 10 13 12 01.09.1993 20,7 16,3 21,4 16,7 13 18 10 13 12 02.09.1993 21,7 15,4 20,5 20,4 20,6 17 10 13 12 03.09.1993 15,7 13,7 15,8 17,4 14,4 17 10 13 12 04.09.1993 14,8 17 14,6 17,7 20 15 10 13 12 05.09.1993 21 9,6 12,1 16,4 12,1 17 10 13 12 06.09.1[...]

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