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Symbolic one-class learning from imbalanced datasets: Application in medical diagnosis
(World Scientic Publishing Company, 2009)
Filter feature selection for one-class classification
(SpringerDordrecht, 2015-12)
In one-class classification problems all training examples belong to a single class. The absence of counter-examples represents a challenge to traditional Machine Learning and pre-processing techniques. This is the case ...
Symbolic one-class learning from imbalanced datasets: Application in medical diagnosis
(World Scientic Publishing Company, 2009)
Detection of adulterants in grape nectars by attenuated total reflectance fourier-transform mid-infrared spectroscopy and multivariate classification strategies
(Universidade Federal de Minas GeraisBrasilFAR - DEPARTAMENTO DE ALIMENTOSICX - DEPARTAMENTO DE QUÍMICAUFMG, 2018)
Multi-class particle swarm model selection for automatic image annotation
(Elsevier Ltd., 2012)
On a Class of Linear Stochastic Heat Equations Driven by Space-Time White Noise
(Centro de Investigación en Matemáticas AC, 2003)
Using the one-vs-one decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems
(ElsevierAmsterdam, 2015-12)
Noise filters are preprocessing techniques designed to improve data quality in classification tasks by detecting and eliminating examples that contain errors or noise. However, filtering can also remove correct examples ...
HCAIM: a discretizer for the hierarchical classification scenario applied to bioinformatics datasets
(Universidade Federal do Ceará, 2018)
Abrupt change detection with One-Class Time-Adaptive Support Vector Machines
(Elsevier, 2013-12-15)
We recently introduced an algorithm for training a sequence of coupled Support Vector Machines which shows promising results in the field of non-stationary classification problems Grinblat, Uzal, Ceccatto, and Granitto ...