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Publikováno v:
Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC). :422-433
Algorithm trading relies on the automatic identification of buying and selling points of a given asset to maximize profit. In this paper, we propose the Trend Classification Trading Algorithm (TCTA) which is based on time series classification and tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aba25c498bd5183070a294e64545e36a
https://doi.org/10.5753/eniac.2021.18272
https://doi.org/10.5753/eniac.2021.18272
Publikováno v:
Expert Systems with Applications. 218:119597
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05eaa4d207bb42175b6f092b41665d9a
https://doi.org/10.1016/j.eswa.2023.119597
https://doi.org/10.1016/j.eswa.2023.119597
Publikováno v:
Information Fusion. 45:66-78
Among the many issues related to data stream applications, those involved in predictive tasks such as classification and regression, play a significant role in Machine Learning (ML). The so-called ensemble-based approaches have characteristics that c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23803bbcfb2f9f9dcdf8a65f159f086a
https://doi.org/10.1016/j.inffus.2018.01.003
https://doi.org/10.1016/j.inffus.2018.01.003
Publikováno v:
Intelligent Systems ISBN: 9783030917012
Tactical asset allocation is an essential method for defining a profitable portfolio for a given period. An analyst usually creates a tactical asset portfolio through technical analysis, a process subjective to the analyst’s knowledge and interpret
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47d787c6ecf78c885d8a5bc244663ec4
https://doi.org/10.1007/978-3-030-91702-9_35
https://doi.org/10.1007/978-3-030-91702-9_35
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Graph-based algorithms have been successfully applied in machine learning and data mining tasks. A simple but, widely used, approach to build graphs from vector-based data is to consider each data instance as a vertex and connecting pairs of it using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb899d424f967b193fea47f86523b61c
https://doi.org/10.1016/j.neunet.2016.09.008
https://doi.org/10.1016/j.neunet.2016.09.008
Autor:
João Roberto Bertini Junior
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 129
Understanding the reason why a prediction has been made by a machine is crucial to grant trust to a human decision-maker. However, data mining based decision support systems are, in general, not designed to promote interpretability; instead, they are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fd599c848019dd867b7f2977b47cace
https://pubmed.ncbi.nlm.nih.gov/32535307
https://pubmed.ncbi.nlm.nih.gov/32535307
Autor:
João Roberto Bertini Junior
Publikováno v:
IJCNN
Data stream mining has attracted much attention of the machine learning community in the last decade. Motivated by the upcoming issues associated with data stream applications, such as concept drift and the velocity into which data needs to be proces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d4a48205bae08da244ebae18ee353f9
https://doi.org/10.1109/ijcnn.2019.8851703
https://doi.org/10.1109/ijcnn.2019.8851703
Autor:
João Roberto Bertini Junior, Mei Abe Funcia, Denis José Schiozer, Antonio Alberto de Souza dos Santos
Publikováno v:
IJCNN
Net Present Value (NPV) measures whether an investment will be profitable within a given period of time. In oil production planning, it consists of an important indicator to evaluate different production strategies. The NPV estimate is calculated on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd98e4b35f810d64e6ca5f2be0680270
https://doi.org/10.1109/ijcnn.2019.8851708
https://doi.org/10.1109/ijcnn.2019.8851708
Publikováno v:
Journal of Artificial Intelligence and Soft Computing Research. 6:119-131
Constructive learning algorithms are an efficient way to train feedforward neural networks. Some of their features, such as the automatic definition of the neural network (NN) architecture and its fast training, promote their high adaptive capacity,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d718f0e76756fe066c2dde3e8ae9a0e
https://doi.org/10.1515/jaiscr-2016-0010
https://doi.org/10.1515/jaiscr-2016-0010