In supervised learning scenarios, some applications require solve a classification problem
wherein labels are not given as a single ground truth. Instead, the criteria of a set of experts …

In recent years, there has been an increasing interest in the design of pattern recognition
systems able to deal with labels coming from multiple sources. To avoid bias during the …

This work introduces a multi-labeler kernel novel approach for data classification learning
from multiple labelers. The learning process is done by training support-vector machine …

This work introduces a multi-labeler kernel novel approach for data classification learning
from multiple labelers. The learning process is done by training support-vector machine …

Actualmente, existe un avance computacional significativo en estrategias de aprendizaje
automático para disciplinas donde se hace necesario la extracción de información en …

La necesidad de mitigar la crisis del cambio climático y suplir la demanda energética, ha
girado la atención hacia las fuentes de energías limpias, como la fotovoltaica. Promoviendo …

This work presents a new method proposal applied to Multi-Labelers scenarios. This is a
situation where labelling individuals in a set of data based on certain characteristics in the …

Actualmente, existe un avance computacional significativo en estrategias de aprendizaje
automático para disciplinas donde se hace necesario la extracción de información en …