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annotate core/tools/machine_learning/cvpartition_alltrain.m @ 0:e9a9cd732c1e tip

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first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 % ---
wolffd@0 2 % fake partitioning for comparison
wolffd@0 3 % to stober08:
wolffd@0 4 % ---
wolffd@0 5 classdef cvpartition_alltrain
wolffd@0 6
wolffd@0 7 properties (Hidden)
wolffd@0 8
wolffd@0 9 mtest;
wolffd@0 10 mtraining;
wolffd@0 11 end
wolffd@0 12 properties
wolffd@0 13 N;
wolffd@0 14 NumTestSets;
wolffd@0 15 TrainSize;
wolffd@0 16 TestSize;
wolffd@0 17 end
wolffd@0 18
wolffd@0 19
wolffd@0 20 methods
wolffd@0 21
wolffd@0 22 % ---
wolffd@0 23 % constuctor: directly calculates the truncated testset
wolffd@0 24 % ---
wolffd@0 25 function P = cvpartition_alltrain(nData, nRuns)
wolffd@0 26
wolffd@0 27 P.NumTestSets = nRuns;
wolffd@0 28 P.N = nData;
wolffd@0 29
wolffd@0 30 % build training and test sets
wolffd@0 31 for i = 1:P.NumTestSets
wolffd@0 32 P.TrainSize(i) = nData;
wolffd@0 33 P.TestSize(i) = nData;
wolffd@0 34 P.mtraining{i} = ones(P.N, 1);
wolffd@0 35 P.mtest{i} = ones(P.N, 1);
wolffd@0 36 end
wolffd@0 37 end
wolffd@0 38
wolffd@0 39 function out = test(P, i)
wolffd@0 40
wolffd@0 41 out = P.mtest{i};
wolffd@0 42 end
wolffd@0 43
wolffd@0 44 function out = training(P, i)
wolffd@0 45
wolffd@0 46 out = P.mtraining{i};
wolffd@0 47 end
wolffd@0 48
wolffd@0 49 end
wolffd@0 50 end