云南高校图书馆联盟文献共享服务平台- CLASSIFIERS

CLASSIFIERS: 作品数：76被引量：75H指数：5; 导出分析报告; 相关领域：自动化与计算机技术更多>>; 相关作者：宋玉张媛昝红英张坤丽马宁更多>>; 相关机构：华南理工大学华北电力大学中国社会科学院北京邮电大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金天津市自然科学基金中国博士后科学基金国家社会科学基金更多>>

Detection and Classification of Diabetic Retinopathy Through Identification of Blood Vessel Thickness Using FOFF & ML Classifiers: 《Journal of Harbin Institute of Technology(New Series)》2024年第6期84-96,共13页G.Indira Devi D.Madhavi; Diabetes is a significant issue in the medical field. The detection and identification of the human eye diseases caused by excessive blood sugar levels in diabetes mellitus are important. The main objective of this st...; 关键词：diabetic retinopathy firefly algorithm optimized Frangi filter KNN SVM

Disseminated tumor cells in bone marrow as predictive classifiers for small cell lung cancer patients: 《Journal of the National Cancer Center》2024年第4期335-345,共11页Ying Wang Jingying Nong Baohua Lu Yuan Gao Mingming Hu Cen Chen Lina Zhang Jinjing Tan Xiaomei Yang Peter Ping Lin Xingsheng Hu Tongmei Zhang; Beijing Municipal Science and Technol-ogy Commission(grant number Z211100002921013);Tongzhou Liang-gao Talents Project(grant number YH201920);Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research In-stitutes(grant number JYY2024-14);Beijing Municipal Public Wel-fare Development and Reform Pilot Project for Medical Research Insti-tutes(grant number JYY2023-15);We thank all participants and their families for supporting this study.; Background: Small cell lung cancer (SCLC) is a highly aggressive disease characterized by early metastasis. Ane- uploid CD31- disseminated tumor cells (DTCs) and CD31+ disseminated tumor endothelial cells (DTECs) resi...; 关键词：Bone marrow Aneuploid DTCs and DTECs SE-iFISH PROGNOSIS SCLC

Multi-Binary Classifiers Using Optimal Feature Selection for Memory-Saving Intrusion Detection Systems: 《Computer Modeling in Engineering & Sciences》2024年第11期1473-1493,共21页Ye-Seul Kil Yu-Ran Jeon Sun-Jin Lee Il-Gu Lee; supported by MOTIE under Training Industrial Security Specialist for High-Tech Industry(RS-2024-00415520);supervised by the Korea Institute for Advancement of Technology(KIAT),and by MSIT under the ICT Challenge and Advanced Network of HRD(ICAN)Program(No.IITP-2022-RS-2022-00156310);supervised by the Institute of Information&Communication Technology Planning&Evaluation(IITP)。; With the rise of remote work and the digital industry,advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics,rendering them difficult to detect with conventional intrus...; 关键词：Endpoint detection and response feature selection machine learning malware detection

Data-Driven Decision-Making for Bank Target Marketing Using Supervised Learning Classifiers on Imbalanced Big Data: 《Computers, Materials & Continua》2024年第10期1703-1728,共26页Fahim Nasir Abdulghani Ali Ahmed Mehmet Sabir Kiraz Iryna Yevseyeva Mubarak Saif; support from the Cyber Technology Institute(CTI)at the School of Computer Science and Informatics,De Montfort University,United Kingdom,along with financial assistance from Universiti Tun Hussein Onn Malaysia and the UTHM Publisher’s office through publication fund E15216.; Integrating machine learning and data mining is crucial for processing big data and extracting valuable insights to enhance decision-making.However,imbalanced target variables within big data present technical challen...; 关键词：Big data machine learning data mining data visualization label encoding imbalanced dataset sampling techniques

Intrusion Detection System Using Classification Algorithms with Feature Selection Mechanism over Real-Time Data Traffic被引量：1: 《China Communications》2024年第9期292-320,共29页Gulab Sah Sweety Singh Subhasish Banerjee; The key objective of intrusion detection systems(IDS)is to protect the particular host or network by investigating and predicting the network traffic as an attack or normal.These IDS uses many methods of machine learn...; 关键词：CICIDS2017 dataset CLASSIFIERS IDS ML NSL KDD dataset RFE

Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis: 《Blockchain(Research and Applications)》2024年第3期106-122,共17页Mohammad Hasan Mohammad Shahriar Rahman Helge Janicke Iqbal H.Sarker; As the use of blockchain for digital payments continues to rise,it becomes susceptible to various malicious attacks.Successfully detecting anomalies within blockchain transactions is essential for bolstering trust in ...; 关键词：Anomaly detection Blockchain Bitcoin transactions Data imbalance Data sampling Explainable AI Machine learning Decision tree Anomaly rules

Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection: 《Computers, Materials & Continua》2024年第8期2917-2939,共23页Islam Zada Mohammed Naif Alatawi Syed Muhammad Saqlain Abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi; This researchwork is supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R411),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.; Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention mechanisms.Supervised machine learning classifiers have emerged as promising tools for malwar...; 关键词：Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

Intelligent Detection and Identification of Attacks in IoT Networks Based on the Combination of DNN and LSTM Methods with a Set of Classifiers: 《Open Journal of Applied Sciences》2024年第8期2296-2319,共24页Brou Médard Kouassi Vincent Monsan Kablan Jérôme Adou; Internet of Things (IoT) networks present unique cybersecurity challenges due to their distributed and heterogeneous nature. Our study explores the effectiveness of two types of deep learning models, long-term memory ...; 关键词：Internet of Things Machine Learning Attack Detection Jamming Deep Learning

Detecting Malicious Uniform Resource Locators Using an Applied Intelligence Framework: 《Computers, Materials & Continua》2024年第6期3827-3853,共27页Simona-Vasilica Oprea Adela Bara; supported by a grant of the Ministry of Research,Innovation and Digitization,CNCS-UEFISCDI,Project Number PN-Ⅲ-P4-PCE-2021-0334,within PNCDI Ⅲ.; The potential of text analytics is revealed by Machine Learning(ML)and Natural Language Processing(NLP)techniques.In this paper,we propose an NLP framework that is applied to multiple datasets to detect malicious Unif...; 关键词：Detecting malicious URL CLASSIFIERS text to feature deep learning ranking algorithms feature building time

Forecasting the Academic Performance by Leveraging Educational Data Mining: 《Intelligent Automation & Soft Computing》2024年第2期213-231,共19页Mozamel M.Saeed; supported via funding from Prince Sattam bin Abdulaziz University Project Number(PSAU/2024/R/1445).; The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collec...; 关键词：Academic achievement AI algorithms CLASSIFIERS data mining deep learning

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

CLASSIFIERS

检索结果分析

下载全文

高级检索检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

CLASSIFIERS

检索结果分析

下载全文

用户登录

高级检索检索式检索