Classification of Cervical Biopsy Images Based on LASSO and EL-SVM by Pan Huang, Shuailei Zhang, Min Li, Jing Wang, Cailing Ma, Bowei Wang, Xiaoyi Lv

“…This paper proposes a method of cervical biopsy tissue image classification based on least absolute shrinkage and selection operator (LASSO) and ensemble learning-support vector machine (EL-SVM). Using the LASSO algorithm for feature selection, the average optimization time was reduced by 35.87 seconds while ensuring the accuracy of the classification, and then serial fusion was performed. …”
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An illustration of multi-class roc analysis for predicting internet addiction among university students. by Nishat Tasnim Thity, Atikur Rahman, Adisha Dulmini, Mst Nilufar Yasmin, Rumana Rois

“…We identified the important features related to IA using the Boruta algorithm. Predictions were made using different machine learning (ML) (decision tree (DT), random forest (RF), support vector machines (SVMs), and logistic regression (LR)) models. …”
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Rockburst Prediction Based on the KPCA-APSO-SVM Model and Its Engineering Application by Yuefeng Li, Chao Wang, Jiankun Xu, Zonghong Zhou, Jianhui Xu, Jianwei Cheng

“…Based on the kernel principal component analysis (KPCA), the adaptive particle swarm optimization (APSO) algorithm, and the support vector machine (SVM), the KPCA-APSO-SVM model was established. …”
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Ensemble modelling reveals spiny monkey orange (Strychnos spinosa Lam.) as a vulnerable wild edible fruit tree in West Africa by Hospice Gérard Gracias Avakoudjo, Mahunan Eric José Vodounnon, Rodrigue Idohou, Aly Coulibaly, Achille Ephrem Assogbadjo

“…Bioclimatic and soil variables were used at a resolution of 30 arcseconds with 588 occurrence records analysed using five algorithms (Random Forest (RF), Maximum Entropy (MaxEnt), Support Vector Machine (SVM), Boosted Regression Trees, and Generalized Linear Model (GLM)) and four global climate models (CanESM5, CNRM-CM6-1, HadGEM3-GC31-LL, and MIROC6). …”
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Ecological Monitoring and Service Value Assessment of River–Lake Shores: A Case Study of the Huanggang and Taihu Segments of the Yangtze River by Xiaoyuan Zhang, Kai Liu, Shudong Wang, Xueke Li

“…The supervised classification results using the support vector machine (SVM) algorithm exceeded 95% accuracy. …”
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A Novel Authentication Management for the Data Security of Smart Grid by Imtiaz Parvez, Maryamossadat Aghili, Hugo Riggs, Aditya Sundararajan, Arif I. Sarwat, Anurag K. Srivastava

“…To implement this node-to-node authentication, One class support vector machine algorithm is proposed which takes advantages of the location information as well as the data transmission history (node identification, packet size, and data transmission frequency). …”
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Google Earth Engine-based Mangrove Mapping and Change Detections for Sustainable Development in Tien Yen District, Quang Ninh Province, Vietnam by M. H. Nguyen, N. T. Nguyen, G. Y. I. Ryadi, M. V. Nguyen, T. L. Duong, C.-H. Lin, T. B. Nguyen

“…Four supervised classification algorithms, including Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes classifier, and Classification and Regression Trees (CART) have been implemented on GEE platform to select the best algorithm to produce spatial-temporal mangrove maps, then change detection of mangroves is performed. …”
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Exploring the role of alternative lengthening of telomere-related genes in diagnostic modeling for non-alcoholic fatty liver disease by Nan Zhu, Xiaoliang Wang, Huiting Zhu, Yue Zheng

“…This study employed a support vector machine algorithm and least absolute shrinkage and selection operator regression analysis to identify key genes for constructing a diagnostic model. …”
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Fusion of microscopic and diffraction images with VGG net for budding yeast recognition in imaging flow cytometry by Yangguang Han, Qifeng Li, Pengpeng Sun, Xiangyun Ma, Yunpeng Yang, Ning Zhang, Jingwen Feng, Yu Sa

“…Paired images were fused with varying weight factors to generate a comprehensive training dataset for a VGG-net-based Convolutional Neural Network (CNN). For comparison, Support Vector Machines (SVM) and Random Forests (RF) based on Grey-Level Co-occurrence Matrix (GLCM) features were employed. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…These optimized features are used for training a multi-class support vector machine, with its parameters further optimized for enhanced classification accuracy. …”
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Mechanisms of three typical endocrine-disrupting chemicals causing myocardial infarction: Gene-level computational modeling by Jing-Xuan Zhou, Shan-Shan Chen, Zi-Yi Zheng, Wang-Bo Yuan, Xiong-Bo Liu, Hong-Gang Ni

“…By combining gene expression data and weighted gene coexpression network analysis (WGCNA), key target genes related to MI were selected and four key hub genes (MAP3K8, PDE4B, BCL2A1 and FGR) were identified by LASSO, support vector machine (SVM) and Boruta algorithm. …”
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The Impact of Simulated Spectral Noise on Random Forest and Oblique Random Forest Classification Performance by Na’eem Hoosen Agjee, Onisimo Mutanga, Kabir Peerbhay, Riyad Ismail

“…This study aimed to evaluate the influence of simulated spectral noise (10%, 20%, and 30%) on random forest (RF) and oblique random forest (oRF) classification performance using two node-splitting models (ridge regression (RR) and support vector machines (SVM)) to discriminate healthy and low infested water hyacinth plants. …”
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Online Modelling and Calculation for Operating Temperature of Silicon-Based PV Modules Based on BP-ANN by Honglu Zhu, Weiwei Lian, Lingxing Lu, Peter Kamunyu, Cao Yu, Songyuan Dai, Yang Hu

“…Due to the above problem, the paper proposes an online method to calculate operating temperature, which adopts the back propagation artificial neural network (BP-ANN) algorithm. The comparative analysis is carried out using data from the empirical test platform, and the results show that both the BP-ANN and the support vector machine (SVM) method can reach good accuracy when the dataset length was over six months. …”
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A practical guide to UAV-based weed identification in soybean: Comparing RGB and multispectral sensor performance by Kelvin Betitame, Cannayen Igathinathane, Kirk Howatt, Joseph Mettler, Cengiz Koparan, Xin Sun

“…In this research, a field study was conducted using a support vector machine classification algorithm and object-based image analysis in ArcGIS Pro to examine the impact of sensor choice on weed type differentiation. …”
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IVIM-DWI-based radiomic model for preoperative prediction of hepatocellular carcinoma differentiation by ZHUANG Yuxiang, LI Xiaofeng, ZHOU Daiquan

“…Support vector machine (SVM), logistic regression (LR) and random forest (RF) algorithms were utilized to construct different image omics models. …”
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Risk prediction model for overall survival in lung cancer based on inflammatory and nutritional markers by Hongqi Zhou, Weiyun Jin, Lindi Li, Xiangwen Nie, Weiwei Wu, Ran Chen, Qizhen Xie, Haixia Wu, Weiwei Jiang, Min Tang, Jinhai Wang, Maoyuan Wang

“…All patients were followed until death or a uniform administrative censoring point.LASSO logistic regression was employed to model the outcome as a binary classification (death within 1 year: yes/no).This study employed a small-sample modeling approach, initially using LASSO regression for feature selection and dimensionality reduction, followed by variance inflation factor and collinearity screening for secondary feature selection. Finally, the Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithm was used to optimize feature variables. …”
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Innovative approaches in marketing for the development of the tourism industry by Yuliia Stasiuk, Andrii Kobchenko

“…For instance, AI-powered chatbots and virtual assistants provide real-time customer support, while machine learning algorithms analyze booking patterns to offer personalized travel recommendations. …”
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Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…The micro-scale backup machine vector algorithm and the high volume resolution soil moisture dispersion map were estimated between 0.18 and 0.46 b. …”
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Monitoring of vegetation chlorophyll content in photovoltaic areas using UAV-mounted multispectral imaging by Ming Li, Weiyi Wang, Haoran Li, Zekun Yang, Jianjun Li

“…The selected features were then used in three modeling strategies—vegetation index–based, texture feature–based, and fused index–texture–based—employing three conventional machine-learning regressors (partial least squares regression, random forest, support vector machine regression) and three deep-learning regressors (back propagation neural network, convolutional neural network, multilayer perceptron). …”
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Debris Flow Susceptibility Prediction Using Transfer Learning: A Case Study in Western Sichuan, China by Tiezhu Li, Qidi Huang, Qigang Chen

“…In this study, debris flow susceptibility models were developed using three machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). …”
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