Many vision problems can be posed as labeling problems in which the solution of a problem is a set of labels assigned to image pixels or features.
We focus on the widely used F measure, defined for binary, single-label problems as the weighted harmonic mean of precision and recall, and later extended to multi-label problems in three ways: macro-averaged, micro-averaged and instance-wise.
The results suggest that when performing classification forecast for data sets of inquiry diagnosis for CHD, ML-kNN achieves better results and it seems to be a practicable solution for multi-label problems in clinical diagnosis in TCM at present.
Conditional Random Fields (CRFs) are probabilistic graphical models widely used for sequence labeling problems in general and NER in particular because they often achieve high performance [ 4, 10, 22].
In the meantime, we present a novel solution to the consistent labeling problem in omnidirectional cameras.
Named entity recognition (NER) is mostly formalized as a sequence labeling problem in which segments of named entities are represented by label sequences.
This ability to freely label government receipts and payments in alternative internally consistent manners renders the government's cash flows meaningless from the perspective of economic theory and is called the labeling problem in economics.
Methods: Wellner et al. treated the de-identification task as a sequence-labeling problem in which labels are assigned to individual words indicating whether the word is the beginning, part of, or end of a particular PHI instance.
In addition, MNet takes into account the unbalanced label problem in protein function prediction, and incorporates a label weighted scheme into the unified objective function to give more emphasis to the functional labels with fewer proteins.
ProMK can selectively integrate multiple networks and can construct an optimal composite network directly targeted to the network based classification, but it suffers from the parameter selection problem, and does not take into account the intrinsic unbalanced label problem in protein function prediction.
