|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
Haohui Lu and Shahadat Uddin
Artificial intelligence is changing the practice of healthcare. While it is essential to employ such solutions, making them transparent to medical experts is more critical. Most of the previous work presented disease prediction models, but did not explai...
ver más
|
|
|
|
|
|
|
Lev Utkin and Andrei Konstantinov
The ensemble-based modifications of the well-known SHapley Additive exPlanations (SHAP) method for the local explanation of a black-box model are proposed. The modifications aim to simplify the SHAP which is computationally expensive when there is a larg...
ver más
|
|
|
|