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Showing 11 of 11 academic articles

Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification

Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam et al. • IEEE Access (2024)

Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable pri...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3400913

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

Boosting Neural Networks

Holger Schwenk, Yoshua Bengio • Neural Computation (2000)

Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, AdaBoost, has been applied with great success to several benchmark machine learning problems using mainly decision tr...

OPENALEX DOI: https://doi.org/10.1162/089976600300015178

Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering (2022)

Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2022.01.012

A Cardiovascular Disease Prediction Model Based on Routine Physical Examination Indicators Using Machine Learning Methods: A Cohort Study

Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine (2022)

BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2022.854287

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE (2024)

Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0314959

Benchmarking Supervised Classifiers for Concurrent Multidomain Dropout-Intention Attributions in Higher Education: Evidence from a Colombian Public University

Marieth Agnes Guillen-García, Osnamir Elias Bru-Cordero, Cristian David Correa-Álvarez • Big Data and Cognitive Computing (2026)

Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...

DOAJ Open Access (DOAJ) DOI: 10.3390/bdcc10080274

Foundations of Machine Learning

• The MIT Press eBooks (2012)

Foundations of Machine LearningSoon we will embark on a theoretical study of AdaBoost in order to understand its properties, particularly its ability as a learning algorithm to generalize, that is, to make accurate predictions on data not s...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.7551/mitpress/8291.003.0006

Machine Learning in Action

Peter de B. Harrington (2012)

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

OPENALEX

A feature selection and scoring scheme for dimensionality reduction in a machine learning task

PHILEMON UTEN EMMOH, christopher ifeanyi Eke, Timothy Moses • Journal of Nigerian Society of Physical Sciences (2025)

Selection of important features is very vital in machine learning tasks involving high-dimensional dataset with large features. It helps in reducing the dimensionality of a dataset and improving model performance. Most of the feature select...

DOAJ Open Access (DOAJ) DOI: 10.46481/jnsps.2025.2273