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Ordinal regression methods: survey and experimental study
(2017-02-03)
Abstract—Ordinal regression problems are those machine learning problems where the objective is to classify patterns using a
categorical scale which shows a natural order between the labels. Many real-world applications ...
Cooperative coevolution of artificial neural network ensembles for pattern classification
(IEEE, 2005)
This paper presents a cooperative coevolutive approach for designing neural network ensembles. Cooperative coevolution is a recent paradigm in evolutionary computation that allows the effective modeling of cooperative ...
Algoritmos genéticos locales
(Universidad de Málaga, 2007)
Los Algoritmos Genéticos Locales son procedimientos
que iterativamente re nan soluciones
dadas. Su diferencia con procedimientos de mejora
iterativa clásicos reside en el uso de operadores
genéticos para realizar el ...
Teaching push-down automata and Turing machines
(2014-02-27)
In this paper we present the new version of a tool to assist in
teaching formal languages and automata theory. In the previous
version the tool provided algorithms for regular expressions, finite
automata and context ...
Exploitation of Pairwise Class Distances for Ordinal Classification
(2013-07-15)
Ordinal classification refers to classification problems in which the classes have a natural
order imposed on them because of the nature of the concept studied. Some ordinal
classification approaches perform a projection ...
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery
(2017-03-30)
This paper approaches the problem of weed mapping for precision agriculture,
using imagery provided by Unmanned Aerial Vehicles (UAVs) from sun
ower
and maize crops. Precision agriculture referred to weed control is ...
Pyramidal Fisher Motion for Multiview Gait Recognition
(2017-01-17)
The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on ...
Borderline kernel based over-sampling
(2017-03-30)
Nowadays, the imbalanced nature of some real-world data
is receiving a lot of attention from the pattern recognition and machine
learning communities in both theoretical and practical aspects, giving
rise to di erent ...
Nonlinear Boosting Projections for Ensemble Construction
(Dale Schuurmans, 2007)
In this paper we propose a novel approach for ensemble construction based on the use of nonlinear
projections to achieve both accuracy and diversity of individual classifiers. The proposed approach
combines the philosophy ...
An ubiquitous and non intrusive system for pervasive advertising using NFC and geolocation technologies and air hand gestures
(Hindawi, 2014)
In this paper we present a pervasive proposal for advertising using mobile phones, Near Field Communication,
geolocation and air hand gestures. Advertising post built by users in public/private spaces can store multiple ...