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Bin Li, Yuqi Wang, Lisha Li and Yande Liu
Machine learning is used widely in near-infrared spectroscopy (NIRS) for fruit qualification. However, the directly split training set used contains redundant samples, and errors may be introduced into the model. Euclidean distance-based and K-nearest ne...
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María Consuelo Sáiz-Manzanares, Ismael Ramos Pérez, Adrián Arnaiz Rodríguez, Sandra Rodríguez Arribas, Leandro Almeida and Caroline Françoise Martin
In recent decades, the use of technological resources such as the eye tracking methodology is providing cognitive researchers with important tools to better understand the learning process. However, the interpretation of the metrics requires the use of s...
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Marcin Blachnik and Miroslaw Kordos
Instance selection and construction methods were originally designed to improve the performance of the k-nearest neighbors classifier by increasing its speed and improving the classification accuracy. These goals were achieved by eliminating redundant an...
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Panagiotis Filippakis, Stefanos Ougiaroglou and Georgios Evangelidis
Reducing the size of the training set, which involves replacing it with a condensed set, is a widely adopted practice to enhance the efficiency of instance-based classifiers while trying to maintain high classification accuracy. This objective can be ach...
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Qingcheng Fan, Sicong Liu, Chunjiang Zhao and Shuqin Li
Feature selection is crucial in classification tasks as it helps to extract relevant information while reducing redundancy. This paper presents a novel method that considers both instance and label correlation. By employing the least squares method, we c...
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Sonia Castelo, Moacir Ponti and Rosane Minghim
Multiple-instance learning (MIL) is a paradigm of machine learning that aims to classify a set (bag) of objects (instances), assigning labels only to the bags. This problem is often addressed by selecting an instance to represent each bag, transforming a...
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Mario Andrés Muñoz and Michael Kirley
In this paper, we investigate how systemic errors due to random sampling impact on automated algorithm selection for bound-constrained, single-objective, continuous black-box optimization. We construct a machine learning-based algorithm selector, which u...
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Werner Mostert, Katherine M. Malan and Andries P. Engelbrecht
This study presents a novel performance metric for feature selection algorithms that is unbiased and can be used for comparative analysis across feature selection problems. The baseline fitness improvement (BFI) measure quantifies the potential value gai...
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Miriam Di Ianni and Giovanna Varricchio
It is well-documented that social networks play a considerable role in information spreading. The dynamic processes governing the diffusion of information have been studied in many fields, including epidemiology, sociology, economics, and computer scienc...
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David Tromp
AbstractEffective selection interviews: The task of line management The selection interview still remains one of the most important and most commonly used selection techniques. During their formal training personnel officials are normally taught how to c...
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David Tromp
AbstractEffective selection interviews: The task of line management The selection interview still remains one of the most important and most commonly used selection techniques. During their formal training personnel officials are normally taught how to c...
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Enrique Díaz de León-Hicks, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss and Hugo Terashima-Marín
In the algorithm selection problem, where the task is to identify the most suitable solving technique for a particular situation, most methods used as performance mapping mechanisms have been relatively simple models such as logistic regression or neural...
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Andrea Sanna, Federico Manuri, Jacopo Fiorenza and Francesco De Pace
Human?robot collaboration (HRC) is a new and challenging discipline that plays a key role in Industry 4.0. Digital transformation of industrial plants aims to introduce flexible production lines able to adapt to different products quickly. In this scenar...
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Luiz Henrique dos Santos Fernandes, Ana Carolina Lorena and Kate Smith-Miles
Various criteria and algorithms can be used for clustering, leading to very distinct outcomes and potential biases towards datasets with certain structures. More generally, the selection of the most effective algorithm to be applied for a given dataset, ...
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Aurora M. Pat-Espadas, Rene Loredo Portales, Leonel E. Amabilis-Sosa, Gloria Gómez and Gladys Vidal
The mining industry is the major producer of acid mine drainage (AMD). The problem of AMD concerns at active and abandoned mine sites. Acid mine drainage needs to be treated since it can contaminate surface water. Constructed wetlands (CW), a passive tre...
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Philipp Hungerländer, Andrea Rendl, Christian Truden
Pág. 492 - 499
The capacitated vehicle routing problem with time windows (cVRPTW) is concerned with finding optimal tours for vehicles that deliver goods to customers within a specific time slot (or time window), respecting the maximal capacity of each vehicle. The on-...
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Ingrid Olesen, Hans B. Bentsen, Michael Phillips and Raul W. Ponzoni
The annual production from global aquaculture has increased rapidly from 2.6 million tons or 3.9% of the total supply of fish, shellfish and mollusks in 1970, to 66.7 million tons or 42.2% in 2012, while capture fisheries have more or less leveled out at...
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Marie Bieber, Wim J. C. Verhagen, Fabrice Cosson and Bruno F. Santos
Spacecraft systems collect health-related data continuously, which can give an indication of the systems? health status. While they rarely occur, the repercussions of such system anomalies, faults, or failures can be severe, safety-critical and costly. T...
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Irina Nizovtseva, Vladimir Palmin, Ivan Simkin, Ilya Starodumov, Pavel Mikushin, Alexander Nozik, Timur Hamitov, Sergey Ivanov, Sergey Vikharev, Alexei Zinovev, Vladislav Svitich, Matvey Mogilev, Margarita Nikishina, Simon Kraev, Stanislav Yurchenko, Timofey Mityashin, Dmitrii Chernushkin, Anna Kalyuzhnaya and Felix Blyakhman
Development of energy-efficient and high-performance bioreactors requires progress in methods for assessing the key parameters of the biosynthesis process. With a wide variety of approaches and methods for determining the phase contact area in gas?liquid...
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Vittorio Maniezzo and Tingting Zhou
The performance of optimization algorithms, and consequently of AI/machine learning solutions, is strongly influenced by the setting of their hyperparameters. Over the last decades, a rich literature has developed proposing methods to automatically deter...
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