Results 11 to 20 of about 35,527 (280)

Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose [PDF]

Frontiers in Cardiovascular Medicine, 2023
BackgroundWith the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention.
Mingyuan Wang, Mingyuan Wang, Yiyi Qian, Yaodong Yang, Haobin Chen, Wei-Feng Rao   +5 more
doaj   +2 more sources

A Stacking Ensemble Learning Framework for Genomic Prediction. [PDF]

Front Genet, 2021
Abstract Background: Machine learning (ML) is perhaps the most useful for the interpretation of large genomic datasets. However, the performance of a single machine learning method in genomic selection (GS) was unsatisfactory in existing research.
Liang M, Chang T, An B, Duan X, Du L, Wang X, Miao J, Xu L, Gao X, Zhang L, Li J, Gao H.   +11 more
europepmc   +6 more sources

Classification of Sleeping Position Using Enhanced Stacking Ensemble Learning. [PDF]

Entropy (Basel)
Sleep position recognition plays a crucial role in enhancing individual sleep quality and addressing sleep-related disorders. However, the conventional non-invasive technology for recognizing sleep positions tends to be limited in its widespread application due to high production and computing costs. To address this issue, an enhanced stacking model is
Xu X, Mo Q, Wang Z, Zhao Y, Li C.
europepmc   +4 more sources

MFDroid: A Stacking Ensemble Learning Framework for Android Malware Detection. [PDF]

Sensors (Basel), 2022
As Android is a popular a mobile operating system, Android malware is on the rise, which poses a great threat to user privacy and security. Considering the poor detection effects of the single feature selection algorithm and the low detection efficiency of traditional machine learning methods, we propose an Android malware detection framework based on ...
Wang X, Zhang L, Zhao K, Ding X, Yu M.
europepmc   +4 more sources

Financial Distress Prediction with Stacking Ensemble Learning

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2022
Previous studies have used financial ratios extensively to build their predictive model of financial distress. The Altman ratio is the most often used to predict, especially in academic studies.
Muhammad Fadhlil Hadi, De-Ron Liang, Tri Kuntoro Priyambodo, Azhari SN   +3 more
doaj   +3 more sources

Enhancing genomic prediction with Stacking Ensemble Learning in Arabica Coffee. [PDF]

Front Plant Sci
Coffee Breeding programs have traditionally relied on observing plant characteristics over years, a slow and costly process. Genomic selection (GS) offers a DNA-based alternative for faster selection of superior cultivars. Stacking Ensemble Learning (SEL) combines multiple models for potentially even more accurate selection.
Nascimento M, Nascimento ACC, Azevedo CF, de Oliveira ACB, Caixeta ET, Jarquin D.   +5 more
europepmc   +4 more sources

Stacking Ensemble Learning Model for Intrusion Detection in Electrical Substation

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Electrical substations are crucial infrastructure in power transmission and distribution but are increasingly vulnerable to cyber threats. However, existing intrusion detection systems (IDS) face challenges such as high false positive rates, limited ...
Mohammad Mahruf Alam, Feddy Setio Pribadi, Rizky Ajie Aprilianto, Arvina Rizqi Nurul’aini   +3 more
doaj   +2 more sources

Code Smell Detection Driven by Hybrid Feature Selection and Ensemble Learning [PDF]

Jisuanji gongcheng, 2022
Code smell is a software feature that violates basic design principles or coding standards.When introduced into a source code, code smell increases the cost and difficulty of its maintenance.Machine learning can outperform other code smell detection ...
AI Chenghao, GAO Jianhua, HUANG Zijie
doaj   +1 more source

Stacked Ensemble Machine Learning for Range-Separation Parameters [PDF]

The Journal of Physical Chemistry Letters, 2021
High-throughput virtual materials and drug discovery based on density functional theory has achieved tremendous success in recent decades, but its power on organic semiconducting molecules suffered catastrophically from the self-interaction error until the optimally tuned range-separated hybrid (OT-RSH) exchange-correlation functionals were developed ...
Cheng-Wei Ju, Ethan J. French, Nadav Geva, Alexander W. Kohn, Zhou Lin   +4 more
openaire   +3 more sources

Improvement of Concrete Crack Segmentation Performance Using Stacking Ensemble Learning

Applied Sciences, 2023
Signs of functional loss due to the deterioration of structures are primarily identified from cracks occurring on the surface of structures, and continuous monitoring of structural cracks is essential for socially important structures.
Taehee Lee, Jung-Ho Kim, Sung-Jin Lee, Seung-Ki Ryu, Bong-Chul Joo   +4 more
doaj   +1 more source