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Machine Learning for Web Intrusion Detection: A Comparative Analysis of Feature Selection Methods mRMR and PFI
(2020-01-01)
Select from the best features in a complex dataset that is a critical task for machine learning algorithms. This work presents a comparative analysis between two resource selection techniques: Minimum Redundancy Maximum ...
A metaheuristic-driven approach to fine-tune Deep Boltzmann Machines
(Elsevier B.V., 2020-12-01)
Deep learning techniques, such as Deep Boltzmann Machines (DBMs), have received considerable attention over the past years due to the outstanding results concerning a variable range of domains. One of the main shortcomings ...
A machine learning strategy for computing interface curvature in Front-Tracking methods
(2022-02-01)
In this work we have described the application of a machine learning strategy to compute the interface curvature in the context of a Front-Tracking framework. Based on angular information of normal and tangential vectors ...
Machine Learning of a Pair of Charged Electrically Particles Inside a Closed Volume: Electrical Oscillations as Memory and Learning of System
(Springer Link, 2022)
In this paper the problem of two charged particles inside a frustum is faced through the principles of Machine Learning compacted by the criteria of Tom Mitchell. In essence, the relevant equations from the classical ...
Optimal transport for machine learning: theory and applications
(2021-03-25)
O que os operadores de produção de petróleo valorizam ao comprar produtos químicos?: uma análise sobre a percepção de valor na decisão de compra ou contratação de um provedor de especialidades químicas no mercado de óleo ...
Machine learning, intelligence (ai and hi) and learning on digital networks
(Universidad Nacional de Educación del Ecuador, 2020)
Machine learning, intelligence (ai and hi) and learning on digital networks
(Universidad Nacional de Educación del Ecuador, 2020)
Machine Learning Classifier Approach with Gaussian Process, Ensemble boosted Trees, SVM, and Linear Regression for 5G Signal Coverage Mapping
This article offers a thorough analysis of the machine learning classifiers approaches for the collected Received Signal Strength Indicator (RSSI) samples which can be applied in predicting propagation loss, used for network ...
Machine learning algorithms to predict core, skin, and hair-coat temperatures of piglets
(Elsevier B.V., 2018-08-01)
Internal-body (core) and surface temperatures of livestock are important information that indicate heat stress status and comfort of animals. Previous studies focused on developing mechanistic and empirical models to predict ...