Zeitschriftenartikel zum Thema „Evaluation of extreme classifiers“
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Balasubramanian, Kishore, und N. P. Ananthamoorthy. „Analysis of hybrid statistical textural and intensity features to discriminate retinal abnormalities through classifiers“. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 233, Nr. 5 (20.03.2019): 506–14. http://dx.doi.org/10.1177/0954411919835856.
Der volle Inhalt der QuelleMichau, Gabriel, Yang Hu, Thomas Palmé und Olga Fink. „Feature learning for fault detection in high-dimensional condition monitoring signals“. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, Nr. 1 (24.08.2019): 104–15. http://dx.doi.org/10.1177/1748006x19868335.
Der volle Inhalt der QuelleRaza, Ali, Furqan Rustam, Hafeez Ur Rehman Siddiqui, Isabel de la Torre Diez, Begoña Garcia-Zapirain, Ernesto Lee und Imran Ashraf. „Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach“. Genes 14, Nr. 1 (26.12.2022): 71. http://dx.doi.org/10.3390/genes14010071.
Der volle Inhalt der QuelleAfolabi, Hassan A., und Aburas A. Abdurazzag. „Statistical performance assessment of supervised machine learning algorithms for intrusion detection system“. IAES International Journal of Artificial Intelligence (IJ-AI) 13, Nr. 1 (01.03.2024): 266. http://dx.doi.org/10.11591/ijai.v13.i1.pp266-277.
Der volle Inhalt der QuelleThiamchoo, Nantarika, und Pornchai Phukpattaranont. „Evaluation of feature projection techniques in object grasp classification using electromyogram signals from different limb positions“. PeerJ Computer Science 8 (06.05.2022): e949. http://dx.doi.org/10.7717/peerj-cs.949.
Der volle Inhalt der QuelleKamaruddin, Ami Shamril, Mohd Fikri Hadrawi, Yap Bee Wah und Sharifah Aliman. „An evaluation of nature-inspired optimization algorithms and machine learning classifiers for electricity fraud prediction“. Indonesian Journal of Electrical Engineering and Computer Science 32, Nr. 1 (01.10.2023): 468. http://dx.doi.org/10.11591/ijeecs.v32.i1.pp468-477.
Der volle Inhalt der QuelleTian, Zhang, Chen, Geng und Wang. „Selective Ensemble Based on Extreme Learning Machine for Sensor-Based Human Activity Recognition“. Sensors 19, Nr. 16 (08.08.2019): 3468. http://dx.doi.org/10.3390/s19163468.
Der volle Inhalt der QuelleGuo, Weian, Yan Zhang, Ming Chen, Lei Wang und Qidi Wu. „Fuzzy performance evaluation of Evolutionary Algorithms based on extreme learning classifier“. Neurocomputing 175 (Januar 2016): 371–82. http://dx.doi.org/10.1016/j.neucom.2015.10.069.
Der volle Inhalt der QuelleAl-Gethami, Khalid M., Mousa T. Al-Akhras und Mohammed Alawairdhi. „Empirical Evaluation of Noise Influence on Supervised Machine Learning Algorithms Using Intrusion Detection Datasets“. Security and Communication Networks 2021 (15.01.2021): 1–28. http://dx.doi.org/10.1155/2021/8836057.
Der volle Inhalt der QuelleOkwonu, Friday Zinzendoff, Nor Aishah Ahad, Nicholas Oluwole Ogini, Innocent Ejiro Okoloko und Wan Zakiyatussariroh Wan Husin. „COMPARATIVE PERFORMANCE EVALUATION OF EFFICIENCY FOR HIGH DIMENSIONAL CLASSIFICATION METHODS“. Journal of Information and Communication Technology 21, No.3 (17.07.2022): 437–64. http://dx.doi.org/10.32890/jict2022.21.3.6.
Der volle Inhalt der QuelleTariq, Muhammad Arham, Allah Bux Sargano, Muhammad Aksam Iftikhar und Zulfiqar Habib. „Comparing Different Oversampling Methods in Predicting Multi-Class Educational Datasets Using Machine Learning Techniques“. Cybernetics and Information Technologies 23, Nr. 4 (01.11.2023): 199–212. http://dx.doi.org/10.2478/cait-2023-0044.
Der volle Inhalt der QuelleJafarzadeh, Hamid, Masoud Mahdianpari, Eric Gill, Fariba Mohammadimanesh und Saeid Homayouni. „Bagging and Boosting Ensemble Classifiers for Classification of Multispectral, Hyperspectral and PolSAR Data: A Comparative Evaluation“. Remote Sensing 13, Nr. 21 (02.11.2021): 4405. http://dx.doi.org/10.3390/rs13214405.
Der volle Inhalt der QuelleTomita, Katsuyuki, Akira Yamasaki, Ryohei Katou, Tomoyuki Ikeuchi, Hirokazu Touge, Hiroyuki Sano und Yuji Tohda. „Construction of a Diagnostic Algorithm for Diagnosis of Adult Asthma Using Machine Learning with Random Forest and XGBoost“. Diagnostics 13, Nr. 19 (27.09.2023): 3069. http://dx.doi.org/10.3390/diagnostics13193069.
Der volle Inhalt der QuelleWalavalkar, Praniket, Ansh Dasrapuria, Meghna Sarda und Lynette Dmello. „A Token-based Approach to Detect Fraud in Ethereum Transactions“. International Journal for Research in Applied Science and Engineering Technology 12, Nr. 4 (30.04.2024): 34–42. http://dx.doi.org/10.22214/ijraset.2024.59690.
Der volle Inhalt der QuelleFAUST, OLIVER, U. RAJENDRA ACHARYA, LIM CHOO MIN und BERNHARD H. C. SPUTH. „AUTOMATIC IDENTIFICATION OF EPILEPTIC AND BACKGROUND EEG SIGNALS USING FREQUENCY DOMAIN PARAMETERS“. International Journal of Neural Systems 20, Nr. 02 (April 2010): 159–76. http://dx.doi.org/10.1142/s0129065710002334.
Der volle Inhalt der QuelleKuntiyellannagari, Bhagyalaxmi, Bhoopalan Dwarakanath und Panuganti VijayaPal Reddy. „Hybrid model for brain tumor detection using convolution neural networks“. Indonesian Journal of Electrical Engineering and Computer Science 33, Nr. 3 (01.03.2024): 1775. http://dx.doi.org/10.11591/ijeecs.v33.i3.pp1775-1781.
Der volle Inhalt der QuelleSakri, Sapiah, und Shakila Basheer. „Fusion Model for Classification Performance Optimization in a Highly Imbalance Breast Cancer Dataset“. Electronics 12, Nr. 5 (28.02.2023): 1168. http://dx.doi.org/10.3390/electronics12051168.
Der volle Inhalt der QuelleDeng, Weiquan, Bo Ye, Jun Bao, Guoyong Huang und Jiande Wu. „Classification and Quantitative Evaluation of Eddy Current Based on Kernel-PCA and ELM for Defects in Metal Component“. Metals 9, Nr. 2 (01.02.2019): 155. http://dx.doi.org/10.3390/met9020155.
Der volle Inhalt der QuelleBibi, Ruqia, Zahid Mehmood, Asmaa Munshi, Rehan Mehmood Yousaf und Syed Sohail Ahmed. „Deep features optimization based on a transfer learning, genetic algorithm, and extreme learning machine for robust content-based image retrieval“. PLOS ONE 17, Nr. 10 (03.10.2022): e0274764. http://dx.doi.org/10.1371/journal.pone.0274764.
Der volle Inhalt der QuelleAl-Awadi, Jhan Yahya Rbat, Hadeel K. Aljobouri und Ali M. Hasan. „MRI Brain Scans Classification Using Extreme Learning Machine on LBP and GLCM“. International Journal of Online and Biomedical Engineering (iJOE) 19, Nr. 02 (16.02.2023): 134–49. http://dx.doi.org/10.3991/ijoe.v19i02.33987.
Der volle Inhalt der QuelleLeng, Qian, Honggang Qi, Jun Miao, Wentao Zhu und Guiping Su. „One-Class Classification with Extreme Learning Machine“. Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/412957.
Der volle Inhalt der QuelleR P, Prawin. „Performance Evaluation and Comparative Analysis of Several Machine Learning Classification Techniques Using a Data-driven Approach in Predicting Renal Failure“. International Journal for Research in Applied Science and Engineering Technology 11, Nr. 6 (30.06.2023): 3522–30. http://dx.doi.org/10.22214/ijraset.2023.54343.
Der volle Inhalt der QuelleK., Bhagyalaxmi, und B. Dwarakanath. „Hybrid model for detection of brain tumor using convolution neural networks“. Computer Science and Information Technologies 5, Nr. 1 (01.03.2024): 78–84. http://dx.doi.org/10.11591/csit.v5i1.p78-84.
Der volle Inhalt der QuelleK., Bhagyalaxmi, und B. Dwarakanath. „Hybrid model for detection of brain tumor using convolution neural networks“. Computer Science and Information Technologies 5, Nr. 1 (01.03.2024): 78–84. http://dx.doi.org/10.11591/csit.v5i1.pp78-84.
Der volle Inhalt der QuelleDing, Hu, Jiaming Na, Shangjing Jiang, Jie Zhu, Kai Liu, Yingchun Fu und Fayuan Li. „Evaluation of Three Different Machine Learning Methods for Object-Based Artificial Terrace Mapping—A Case Study of the Loess Plateau, China“. Remote Sensing 13, Nr. 5 (08.03.2021): 1021. http://dx.doi.org/10.3390/rs13051021.
Der volle Inhalt der QuelleYotsawat, Wirot, Pakaket Wattuya und Anongnart Srivihok. „Improved credit scoring model using XGBoost with Bayesian hyper-parameter optimization“. International Journal of Electrical and Computer Engineering (IJECE) 11, Nr. 6 (01.12.2021): 5477. http://dx.doi.org/10.11591/ijece.v11i6.pp5477-5487.
Der volle Inhalt der QuelleHe, Qingshan, Jianping Yang, Hongju Chen, Jun Liu, Qin Ji, Yanxia Wang und Fan Tang. „Evaluation of Extreme Precipitation Based on Three Long-Term Gridded Products Over the Qinghai-Tibet Plateau“. Remote Sensing 13, Nr. 15 (30.07.2021): 3010. http://dx.doi.org/10.3390/rs13153010.
Der volle Inhalt der QuellePhotiadou, C. S., A. H. Weerts und B. J. J. M. van den Hurk. „Evaluation of two precipitation data sets for the Rhine River using streamflow simulations“. Hydrology and Earth System Sciences 15, Nr. 11 (08.11.2011): 3355–66. http://dx.doi.org/10.5194/hess-15-3355-2011.
Der volle Inhalt der QuelleNida, Nudrat, Muhammad Haroon Yousaf, Aun Irtaza und Sergio A. Velastin. „Instructor Activity Recognition through Deep Spatiotemporal Features and Feedforward Extreme Learning Machines“. Mathematical Problems in Engineering 2019 (30.04.2019): 1–13. http://dx.doi.org/10.1155/2019/2474865.
Der volle Inhalt der QuelleAlshammari, Khaznah, Shah Muhammad Hamdi und Soukaina Filali Boubrahimi. „Identifying Flare-indicative Photospheric Magnetic Field Parameters from Multivariate Time-series Data of Solar Active Regions“. Astrophysical Journal Supplement Series 271, Nr. 2 (19.03.2024): 39. http://dx.doi.org/10.3847/1538-4365/ad21e4.
Der volle Inhalt der QuellePinki, Farhana Tazmim, Md Abdul Awal, Khondoker Mirazul Mumenin, Md Shahadat Hossain, Jabed Al Faysal, Rajib Rana, Latifah Almuqren, Amel Ksibi und Md Abdus Samad. „HGSOXGB: Hunger-Games-Search-Optimization-Based Framework to Predict the Need for ICU Admission for COVID-19 Patients Using eXtreme Gradient Boosting“. Mathematics 11, Nr. 18 (18.09.2023): 3960. http://dx.doi.org/10.3390/math11183960.
Der volle Inhalt der QuelleGhorbani, Aida, Amir Daneshvar, Ladan Riazi und Reza Radfar. „Friend Recommender System for Social Networks Based on Stacking Technique and Evolutionary Algorithm“. Complexity 2022 (31.08.2022): 1–11. http://dx.doi.org/10.1155/2022/5864545.
Der volle Inhalt der QuelleHao, Yong Xing, Ya Mei Han, Hai Tao Cheng und Hua Ying Guo. „The Stability Evaluation of Radial Ring Rolling“. Advanced Materials Research 482-484 (Februar 2012): 1229–32. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.1229.
Der volle Inhalt der QuelleQin, Chao, Yunfeng Zhang, Fangxun Bao, Caiming Zhang, Peide Liu und Peipei Liu. „XGBoost Optimized by Adaptive Particle Swarm Optimization for Credit Scoring“. Mathematical Problems in Engineering 2021 (23.03.2021): 1–18. http://dx.doi.org/10.1155/2021/6655510.
Der volle Inhalt der QuelleShahi, T. B., C. Sitaula und N. Paudel. „A Hybrid Feature Extraction Method for Nepali COVID-19-Related Tweets Classification“. Computational Intelligence and Neuroscience 2022 (09.03.2022): 1–11. http://dx.doi.org/10.1155/2022/5681574.
Der volle Inhalt der QuellePyko, N. S., E. D. Orandarenko und M. I. Bogachev. „Statistical Analysis of Local Extrema in Rough Sea Surfaces Based on Computer Simulation“. Journal of the Russian Universities. Radioelectronics 26, Nr. 5 (28.11.2023): 99–111. http://dx.doi.org/10.32603/1993-8985-2023-26-5-99-111.
Der volle Inhalt der QuelleMolla, Shourav, F. M. Javed Mehedi Shamrat, Raisul Islam Rafi, Umme Umaima, Md Ariful Islam Arif, Shahed Hossain und Imran Mahmud. „A predictive analysis framework of heart disease using machine learning approaches“. Bulletin of Electrical Engineering and Informatics 11, Nr. 5 (01.10.2022): 2705–16. http://dx.doi.org/10.11591/eei.v11i5.3942.
Der volle Inhalt der QuelleJayaraman, Senthil Kumar, Venkataraman Venkatachalam, Marwa M. Eid, Kannan Krithivasan, Sekar Kidambi Raju, Doaa Sami Khafaga, Faten Khalid Karim und Ayman Em Ahmed. „Enhancing Cyclone Intensity Prediction for Smart Cities Using a Deep-Learning Approach for Accurate Prediction“. Atmosphere 14, Nr. 10 (16.10.2023): 1567. http://dx.doi.org/10.3390/atmos14101567.
Der volle Inhalt der QuelleKek, Tomaž, Primož Potočnik, Martin Misson, Zoran Bergant, Mario Sorgente, Edvard Govekar und Roman Šturm. „Characterization of Biocomposites and Glass Fiber Epoxy Composites Based on Acoustic Emission Signals, Deep Feature Extraction, and Machine Learning“. Sensors 22, Nr. 18 (13.09.2022): 6886. http://dx.doi.org/10.3390/s22186886.
Der volle Inhalt der QuelleKorvink, Michael, John Martin und Michael Long. „Real-Time Identification of Patients Included in the CMS Bundled Payment Care Improvement (BPCI) Program“. Infection Control & Hospital Epidemiology 41, S1 (Oktober 2020): s367—s368. http://dx.doi.org/10.1017/ice.2020.993.
Der volle Inhalt der QuelleSampath, Akila, Uma S. Bhatt, Peter A. Bieniek, Robert Ziel, Alison York, Heidi Strader, Sharon Alden et al. „Evaluation of Seasonal Forecasts for the Fire Season in Interior Alaska“. Weather and Forecasting 36, Nr. 2 (April 2021): 601–13. http://dx.doi.org/10.1175/waf-d-19-0225.1.
Der volle Inhalt der QuelleAlitalesi, Atefe, Hamid Jazayeriy und Javad Kazemitabar. „Wi-Fi fingerprinting-based floor detection using adaptive scaling and weighted autoencoder extreme learning machine“. Computer Science and Information Technologies 3, Nr. 2 (01.07.2022): 104–15. http://dx.doi.org/10.11591/csit.v3i2.p104-115.
Der volle Inhalt der QuelleAtefe Alitaleshi, Hamid Jazayeriy und Javad Kazemitabar. „Wi-Fi fingerprinting-based floor detection using adaptive scaling and weighted autoencoder extreme learning machine“. Computer Science and Information Technologies 3, Nr. 2 (01.07.2022): 104–15. http://dx.doi.org/10.11591/csit.v3i2.pp104-115.
Der volle Inhalt der QuelleHüllermeier, Eyke, Marcel Wever, Eneldo Loza Mencia, Johannes Fürnkranz und Michael Rapp. „A flexible class of dependence-aware multi-label loss functions“. Machine Learning 111, Nr. 2 (13.01.2022): 713–37. http://dx.doi.org/10.1007/s10994-021-06107-2.
Der volle Inhalt der QuelleKodati, Dr Sarangam, Dr M. Dhasaratham, Veldandi Srikanth und K. Meenendranath Reddy. „Classification of SARS Cov-2 and Non-SARS Cov-2 Pneumonia Using CNN“. Journal of Prevention, Diagnosis and Management of Human Diseases, Nr. 36 (23.11.2023): 32–40. http://dx.doi.org/10.55529/jpdmhd.36.32.40.
Der volle Inhalt der QuelleSugiharti, Endang, Riza Arifudin, Dian Tri Wiyanti und Arief Broto Susilo. „Integration of convolutional neural network and extreme gradient boosting for breast cancer detection“. Bulletin of Electrical Engineering and Informatics 11, Nr. 2 (01.04.2022): 803–13. http://dx.doi.org/10.11591/eei.v11i2.3562.
Der volle Inhalt der QuelleOmar Franklin Molina, Zeila Coelho Santos, Bruno Ricardo Huber Simião, Rógerio Ferreira Marchezan, Natalia de Paula e Silva und Karla Regina Gama. „A comprehensive method to classify subgroups of bruxers in temporomandibular disorders (TMDs) individuals: frequency, clinical and psychological implications“. RSBO 10, Nr. 1 (28.03.2014): 11–9. http://dx.doi.org/10.21726/rsbo.v10i1.888.
Der volle Inhalt der QuelleM, Duraipandian, und Vinothkanna R. „Smart Digital Mammographic Screening System for Bulk Image Processing“. December 2020 2, Nr. 4 (22.02.2021): 156–61. http://dx.doi.org/10.36548/jeea.2020.4.003.
Der volle Inhalt der QuelleAcosta-Coll, Melisa, Abel Morales, Ronald Zamora-Musa und Shariq Aziz Butt. „Cross-Evaluation of Reflectivity from NEXRAD and Global Precipitation Mission during Extreme Weather Events“. Sensors 22, Nr. 15 (02.08.2022): 5773. http://dx.doi.org/10.3390/s22155773.
Der volle Inhalt der QuelleT R, Prajwala. „NON-PARAMETRIC RANDOMIZED TREE CLASSIFIER FOR DETECTION OF AUTISM DISORDER IN TODDLERS“. International Journal of Research -GRANTHAALAYAH 9, Nr. 10 (03.11.2021): 205–10. http://dx.doi.org/10.29121/granthaalayah.v9.i10.2021.4341.
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