📄 train_test_simple.m
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function run = train_test_simple(X, Y, trainindex, testindex, classifier)
global preprocess;
clear run;
% The statistics of dataset
num_class = length(preprocess.ClassSet);
class_set = preprocess.ClassSet;
% Extract the training and testing data
X_test = X(testindex, :);
Y_test = Y(testindex, :);
X_train = X(trainindex, :);
Y_train = Y(trainindex, :);
% Classify with Ensemble
[Y_compute, Y_prob] = Classify(classifier, X_train, Y_train, X_test, Y_test, num_class);
run.Y_compute = Y_compute; run.Y_prob = Y_prob; run.Y_test = Y_test;
% Aggregate the predictions in a shot
% if (preprocess.ShotAvailable == 1), [Y_compute, Y_prob, Y_test] = AggregatePredByShot(Y_compute, Y_prob, Y_test, testindex); end;
% Report the performance
[run.YY, run.YN, run.NY, run.NN, run.Prec, run.Rec, run.F1, run.Err] = CalculatePerformance(Y_compute, Y_test, class_set);
if ((preprocess.ComputeMAP == 1) && (length(preprocess.OrgClassSet) == 2)),
TrueYprob = Y_prob .* (Y_compute == 1) + (1 - Y_prob) .* (Y_compute ~= 1);
run.AvgPrec = ComputeAP(TrueYprob, Y_test, class_set);
run.BaseAvgPrec = ComputeRandAP(Y_test, class_set);
fprintf('AP:%f, Base:%f\n', run.AvgPrec, run.BaseAvgPrec);
end;
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