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41
Oversampling techniques for imbalanced data in regression
Published 2024“…<p>Our study addresses the challenge of imbalanced regression data in Machine Learning (ML) by introducing tailored methods for different data structures. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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masterThesis -
44
Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering
Published 2024“…It calculates the dimension relevance with various data instances. These further place the relevant dimension samples in one group. …”
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45
Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. …”
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46
Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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47
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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doctoralThesis -
51
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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52
Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review
Published 2019Subjects: -
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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doctoralThesis -
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55
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
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doctoralThesis -
57
Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023“…PubMed, Google Scholar, Science Direct, BioRXiv, and MedRxiv were explored to identify relevant articles. Study selection and data extraction were independently conducted by 2 reviewers. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data
Published 2024“…The Experience API (xAPI) provides a comprehensive mechanism to document all types of learning interactions, storing this stream of data into the Learning Record Store (LRS). …”
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Nested ensemble selection: An effective hybrid feature selection method
Published 2023“…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …”
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