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SETLABELS
A = SETLABELS(A,LABELS,J)
W = SETLABELS(W,LABELS,J)
Input | |
A | Input dataset, size [M,K] |
W | Input mapping (classifier), size [K,C] |
LABELS | Desired labels. M or length(J) labels for a dataset. |
C | or length(J) labels for a mapping. |
Output | |
A | Dataset with reset labels |
W | Mapping with reset labels |
The labels of the dataset A are reset by LABELS. If supplied, the index vector J defines the objects for wich LABELS applies. If in LABELS just a single label is given all the objects defined by J are given that label. If LABELS is empty ([]) or NaN all the objects defined by J are marked as unlabeled.
If A has soft labels (label type is 'soft') or has no labels but targets (label type is 'targets'), these soft labels or targets are replaced by LABELS, provided it has the right size.
For soft labels and targets supplied to relabel a dataset, LABELS may be supplied as a dataset of which the data are used for the soft labels or targets and the feature labels are used to set LABLIST of A.
The labels stored in a classifier mapping W are assigned as feature labels of the resulting dataset D in case a dataset B is applied to W
D = A*W.
datasets, mappings, multi_labeling,
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