Results 131 to 140 of about 150,441 (331)

Stroke Prediction Using XGboost and a Fusion of XGboost with Random Forest

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Abstract - Stroke is a life-threatening medical condition caused by disrupted blood flow to the brain, representing a major global health concern with significant health and economic consequences. Researchers are working to tackle this challenge by developing automated stroke prediction algorithms, which can enable timely interventions and potentially ...
openaire   +1 more source

Shapley Additive Explanation for Local Class Differentiation: Local Explainability for Class Differentiation in Classification Models

Advanced Intelligent Systems, EarlyView.
An instance‐level, model‐agnostic explanation of class differentiation is introduced through SHAP‐LCD, linking probability shifts to feature‐wise Shapley contributions. The method operates on tabular and image data and is released in a fully reproducible implementation, offering a transparent way to examine, at each instance, why predictive models ...
Roxana M. Romero Luna, Hugo A. Ordoñez Erazo, Carlos A. Cobos Lozada   +2 more
wiley   +1 more source

AN OPTIMIZED XGBOOST FOR FALSE POSITIVE REDUCTION IN A NETWORK INTRUSION DETECTION

Academy Journal of Science and Engineering
Cybersecurity operations are increasingly challenged by large volume of false alerts produced by Intrusion Detection Systems (IDS) which leads to analyst fatigue and increases the likelihood of missing real threats.
Adeola O. Kolawole, Emake Imokhai, Martins E. Irhebhude   +2 more
doaj   +1 more source

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism

Annals of Neurology, EarlyView.
Objective Pre‐mortem diagnosis of parkinsonism is often challenging due to atypical presentations, overlapping syndromes, and co‐pathologies. This study aimed to develop a machine learning‐based algorithm predicting neuropathology in parkinsonism using chronological clinical presentations, which has previously been underexplored.
Daisuke Ono, Hiroaki Sekiya, Alexia R. Maier, Neill R. Graff‐Radford, Zbigniew K. Wszolek, Dennis W. Dickson   +5 more
wiley   +1 more source

Comparative Study on the Identification Methods of Tight Gas Reservoir Fluids Based on Machine Learning

Cejing jishu
To improve the reliability of fluid identification in tight gas reservoirs, address the reduced contribution of logging parameters caused by geological factors, and provide support for oil and gas exploration and development, taking a tight reservoir ...
LIU Hongrui, YANG Bin, DAI Xingyu, PU Jincheng, TANG Shengshou   +4 more
doaj   +1 more source

Use of Machine Learning to Identify Markers of Risk for Fragile X‐Associated Tremor/Ataxia Syndrome: A Preliminary Analysis

Annals of Neurology, EarlyView.
Objective The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of Fragile X‐associated tremor/ataxia syndrome (FXTAS) among male fragile X premutation carriers (PCs). Methods We explored neuropsychological and motor evaluation metrics, brain magnetic resonance imaging ...
Chitrabhanu Gupta, Angeela Poudel, Jun Yi Wang, Randi Hagerman, Glenda Espinal, Jessica Famula, Andrea Schneider, Flora Tassone, Susan M. Rivera, Chen‐Nee Chuah, David Hessl   +10 more
wiley   +1 more source

Machine Learning Models for Predicting Mechanical Properties in Friction Stir Welding of Al Alloys

Annals of "Dunarea de Jos" University of Galati, Fascicle XII, Welding Equipment and Technology
Friction Stir Welding (FSW) has developed as an extremely reliable solid-state joining technique for Al alloys, which possesses superior mechanical properties and minimal defects compared to conventional fusion welding.
B. Gugulothu, K. Srividya, S. Vijayakumar, I. Veeranjaneyulu, S. Revathi, M. Ramya   +5 more
doaj   +1 more source

The Optuna–LightGBM–XGBoost Model: A Novel Approach for Estimating Carbon Emissions Based on the Electricity–Carbon Nexus

Applied Sciences
With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact.
Yu Cai, Jianxin Feng, Yanqing Wang, Yuanming Ding, Yue Hu, Hui Fang   +5 more
semanticscholar   +1 more source

Prediction of Properties of Polymer Composite Formulations Using Ensemble Models With Feature Generation

Journal of Applied Polymer Science, EarlyView.
This study develops an interpretable machine‐learning framework to predict multiple properties of polymer composites based on composition and processing variables. By combining ensemble models with composition‐based feature generation and SHAP‐based interpretation, the approach reveals composition‐property relationships and supports efficient multi ...
Dong Ryeol Shin, Sung Kwang Lee
wiley   +1 more source

A combined approach to pixel-wise classification of satellite images based on LBP, pseudocolor features, and XGBOOST

Радіоелектронні і комп'ютерні системи
The subject of the article is pixel-wise classification of Sentinel-2 satellite imagery represented as three-channel data mapped to the RGB color space for convenient visualization, with specific attention to the challenges posed by sensor noise and ...
Maksym Rybnytskyi, Sergii Kryvenko, Volodymyr Lukin, Volodymyr Rebrov   +3 more
doaj   +1 more source