SPIDER The Spider Objects
Group object A=GROUP(I,[G]) returns a group object initialized with a cell array of algorithms I and an optional grouping type G. This is used to collect a group of algorithms. Examples: group({svm knn c45}), get_mean(train(cv(group({svm knn })),train(toy))) Hyperparameter group='all' This parameter stores grouping type: 'one_for_each', 'all' or 'separate' (default='all'). When results of training and testing are output by a (grouped) algorithm, they are stored in the same group type given here. This is important for objects like chain, and get_mean which do not deal with data objects separately. GROUP TYPE 'all': each item is passed independently and separately to all training objects, e.g d=gen(toy); a=group({knn svm}); train(a,group({d d},'separate')) gives 4 outputs. 'one_for_each': the n^th data item is passed to the n^th training object in an group object, e.g d=gen(toy);g=group({d d},'one_for_each'); a=group({knn svm}); train(a,g) gives 2 outputs. 'all': passes all the data objects to a single training object, e.g d=gen(toy); a=group({knn svm}); r=train(a,d); train(get_mean,group(r,'all')) gives 1 ouput. [NOTE: It is also possible to use the transpose operator with group, e.g: r=group({ {svm svm} {knn knn} })' will give the same result as group({ {svm knn} {svm knn} })]