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Labeling association rule clustering through a genetic algorithm approach
(2014-01-01)
Among the post-processing association rule approaches, a promising one is clustering. When an association rule set is clustered, the user is provided with an improved presentation of the mined patterns, since he can have ...
A framework to generate synthetic multi-label datasets
(ElsevierAmsterdam, 2014-02-25)
A controlled environment based on known properties of the dataset used by a learning algorithm is useful to empirically evaluate machine learning algorithms. Synthetic (artificial) datasets are used for this purpose. ...
Synthesis and pharmacological properties of TOAC-labeled angiotensin and bradykinin analogs
(Elsevier B.V., 2002-01-01)
Angiotensin II (AngII) and bradykinin (BK) derivatives containing the TOAC (2,2,6,6-tetramethylpiperidine-N-oxyl-4-amino-4-carboxylic acid) spin label were synthesized by solid phase methodology. Ammonium hydroxide (pH 10, ...
A framework for multi-label exploratory data analysis: ML-EDA
(Universidad de la RepúblicaUniversidad Católica del UruguayUniversidad ORT UruguayUniversidad de MontevideoUniversidad de la EmpresaMontevideo, 2014-09)
Most supervised learning methods consider that each dataset instance is associated with a unique label. However, there are several domains in which the instances are associated with a set of labels (a multi-label). An ...
Antibody Labeling with Remazol Brilliant Violet 5R, a vinylsulphonic reactive dye
(Taylor & Francis, 2012-09)
Colloidal gold is the first choice for labeling antibodies to be used in Point Of Care Testing. However, there are some recent reports on a family of textile dyes—named “reactive dyes”—being suitable for protein labeling. ...
Evaluating loss minimization in multi-label classification via stochastic simulation using beta distribution
(Universidade Federal do Espírito SantoBRPrograma de Pós-Graduação em InformáticaUFESMestrado em Informática, 2016-05-20)
The objective of this work is to present the effectiveness and efficiency of algorithms for solving the loss minimization problem in Multi-Label Classification (MLC). We first prove that a specific case of loss minimization ...