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Mostrando ítems 1-10 de 43
Artículo
On the evolutionary weighting of neighbours and features in the k-nearest neighbour rule
(Elsevier, 2019)
This paper presents an evolutionary method for modifying the behaviour of the k-Nearest-Neighbour clas sifier (kNN) called Simultaneous Weighting of Attributes and Neighbours (SWAN). Unlike other weighting methods, SWAN ...
Artículo
Selecting the best measures to discover quantitative association rules
(Elsevier, 2014)
The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly ...
Artículo
Obtaining optimal quality measures for quantitative association rules
(Elsevier, 2016)
There exist several works in the literature in which fitness functions based on a combination of weighted measures for the discovery of association rules have been proposed. Nevertheless, some differences in the measures ...
Artículo
EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion
(Elsevier, 2012)
Land use and land covers (LULC) maps are remote sensing products that are used to classify areas into different landscapes. Data fusion for remote sensing is becoming an important tool to improve classical approaches. ...
Artículo
Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems
(Elsevier, 2013)
This paper combines feature selection methods with a two-stage evolutionary classifier based on product unit neural networks. The enhanced methodology has been tried out with four filters using 18 data sets that report ...
Artículo
Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
(MDPI, 2018)
New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent ...
Artículo
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
(Elsevier, 2018)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. However, this task is becoming a challenge because the processing power of most existing techniques ...
Artículo
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks
(MDPI, 2019)
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques ...
Artículo
Evolutionary association rules for total ozone content modeling from satellite observations
(Elsevier, 2011)
In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association Rules) that extends a recently published algorithm by the authors and we describe its ap plication ...
Artículo
Searching for rules to detect defective modules: A subgroup discovery approach
(Elsevier, 2012)
Data mining methods in software engineering are becoming increasingly important as they can support several aspects of the software development life-cycle such as quality. In this work, we present a data mining approach ...