Comparative analysis of machine learning algorithms for predicting depression among individuals with diabetes by Hind Bourkhime, Noura Qarmiche, Soumaya Benmaamar, Nada Lazar, Mohammed Omari, Mohamed Berraho, Nabil Tachfouti, Samira El Fakir, Hanan El Ouahabi, Nada Otmani

“…The algorithms evaluated include logistic regression (LR), k-nearest neighbors (KNN), decision tree (DT), random forest (RF), Adaptive Boosting (AdaBoost), support vector machine (SVM), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost). …”
Get full text

Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

“…The classification of the two Iberian strains reached the highest mean AUROC of 0.83 using Support Vector Machine (SVM) model. The most relevant genera in this classification performance were Acetitomaculum, Butyricicoccus and Limosilactobacillus. …”
Get full text

rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…Temperature readings are labeled and stored for analysis, while audio data is classified into breathing, coughing, and speaking categories using the Support Vector Machine (SVM) algorithm. The SVM’s performance is further optimized using the Lion Algorithm. …”
Get full text

A Method of Intelligent Driving-Style Recognition Using Natural Driving Data by Siyang Zhang, Zherui Zhang, Chi Zhao

Get full text

Discrimination of Customers Decision-Making in a Like/Dislike Shopping Activity Based on Genders: A Neuromarketing Study by Atefe Hassani, Amin Hekmatmanesh, Ali Motie Nasrabadi

“…The identifications of Like/Dislike conditions were then facilitated by the Support Vector Machine, Random Forest, Linear Discriminant Analysis, and K-Nearest Neighbors classifiers. …”
Get full text

Integrating spatiotemperporal features into fault prediction using a multi-dimensional method by Chun-Yi Lin, Yu-Chuan Tseng, Wu-Sung Yao

“…It integrates vibration and current data, analyzes spatiotemporal characteristics, and uses support vector machines and random forest algorithms to analyze fault characteristics. …”
Get full text

Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RFR), a Genetic Algorithm (GA) for optimization, and Response Surface Methodology (RSM) for statistical modeling were used to analyze a dataset of 60 observations. …”
Get full text

Enhanced Kidney Stone Detection and Classification Using SVM and LBP Features by Hawkar K. Hama, Hamsa D. Majeed, Goran Saman Nariman

“…The Local Binary Pattern (LBP) technique, combined with the support vector machine (SVM) algorithm serves as the primary components of the proposed model. …”
Get full text

An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments by Zhenling Dai, Ziqun Gu, Rongrong Shen, Jingshuai Wang

Get full text

ANALISIS KINERJA MODEL STACKING BERBASIS RANDOM FOREST DAN SVM DALAM KLASIFIKASI RUMAH TANGGA BERDASARKAN GARIS KEMISKINAN MAKANAN DI PROVINSI JAWA BARAT by Ghardapaty Ghaly Ghiffary, Nabila Tri Amanda, Rizky Ardhani, Bagus Sartono, Aulia Rizki Firdawanti

“…This research applies the stacking method with two machine learning algorithms, namely Random Forest and Support Vector Machine (SVM) as base learners and logistic regression as a meta learner. …”
Get full text

Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

“…The ML techniques include random forest (RF), support vector machine (SVM), decision tree (DT), and the deep learning approach entails artificial neural networks (ANN). …”
Get full text

Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
Get full text

Investigation of an Optimized Linear Regression Model with Nonlinear Error Compensation for Tool Wear Prediction by Lihua Shen, Baorui Du, He Fan, Hailong Yang

Get full text

Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers by Firman Aziz, Mutia Maulida, Jafar Jafar, Nurafni Shahnyb, Norma Nasir, Ampauleng Ampauleng

“…The proposed Ensemble Least Squares Support Vector Machine (ELS-SVM) algorithm demonstrated superior performance compared to traditional SVM and LS-SVM methods. …”
Get full text

Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Next, in view of the problem that the standard least squares support vector machine has no regularization term, a method to improve the modeling ro-bustness was proposed by introducing the IGGⅢ weighting function into the obtained sparse least squares support vector regression (S-LS-SVR) model. …”
Get full text

Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…In this paper, we introduce a novel imbalanced learning approach named Imbalanced Maximizing-Area Under the Curve (AUC) Proximal Support Vector Machine (ImAUC-PSVM), which harnesses the foundational principles of traditional PSVM for the detection of CVDs. …”
Get full text

Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…Edge computing allows to do AI processing on devices with limited resources, but the challenge remains high computational costs followed by the energy limitations of such devices making on-device machine learning inefficient, especially for Support Vector Machine (SVM) classifiers. …”
Get full text

Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Methods: This study presents a hybrid method integrating residual network (ResNet50), grey wolf optimization (GWO), and machine learning classifiers such as multi-layer perceptron (MLP) and support vector machine (SVM) to improve classification performance. …”
Get full text

Prediction of contact resistance of electrical contact wear using different machine learning algorithms by Zhen-bing Cai, Chun-lin Li, Lei You, Xu-dong Chen, Li-ping He, Zhong-qing Cao, Zhi-nan Zhang

“…To reduce testing time and costs and quickly obtain the electrical contact performance of H62 brass alloy after wear caused by different factors, three algorithms (random forest (RF), support vector regression (SVR), and BP neural network (BPNN)) were used to train and test experimental results, resulting in a machine learning model suitable for predicting the stable mean resistance of H62 brass alloy after wear. …”
Get full text

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis by Jingtai Ma, Jingtai Ma, Yiting Fang, Yiting Fang, Shiqi Li, Shiqi Li, Lilian Zeng, Siyi Chen, Zhifeng Li, Guiyuan Ji, Xingfen Yang, Wei Wu, Wei Wu

Get full text