云南高校图书馆联盟文献共享服务平台- UNDERSAMPLING

UNDERSAMPLING: 作品数：11被引量：11H指数：3; 导出分析报告; 相关领域：自动化与计算机技术更多>>; 相关机构：四川大学华西医院南京邮电大学更多>>; 相关期刊：《Journal of Beijing Institute of Technology》《Chinese Physics B》《Science China(Information Sciences)》《Journal of Intelligent Learning Systems and Applications》更多>>; 相关基金：国家自然科学基金国家高技术研究发展计划北京市自然科学基金更多>>

Multi-Class Sentiment Analysis of Social Media Data with Machine Learning Algorithms: 《Computers, Materials & Continua》2021年第10期913-930,共18页Galimkair Mutanov Vladislav Karyukin Zhanl Mamykova; The volume of social media data on the Internet is constantly growing.This has created a substantial research field for data analysts.The diversity of articles,posts,and comments on news websites and social networks a...; 关键词：Social media sentiment analysis imbalanced classes machine learning OVERSAMPLING UNDERSAMPLING SMOTE RUSSIAN KAZAKH

Credit Card Fraud Detection Using Weighted Support Vector Machine被引量：3: 《Applied Mathematics》2020年第12期1275-1291,共17页Dongfang Zhang Basu Bhandari Dennis Black; Credit card fraudulent data is highly imbalanced, and it has presented an overwhelmingly large portion of nonfraudulent transactions and a small portion of fraudulent transactions. The measures used to judge the verac...; 关键词：Support Vector Machine Binary Classification Imbalanced Data UNDERSAMPLING Credit Card Fraud

Important sampling based active learning for imbalance classification: 《Science China(Information Sciences)》2020年第8期192-205,共14页Xinyue WANG Bo LIU Siyu CAO Liping JING Jian YU; National Natural Science Foundation of China(Grant Nos.61822601,61773050,61632004,61972132);Beijing Natural Science Foundation(Grant No.Z180006);National Key Research and Development Program(Grant No.2017YFC1703506);Fundamental Research Funds for the Central Universities(Grant Nos.2019JBZ110,2019YJS040);Youth Foundation of Hebei Education Department(Grant No.QN2018084);Science and Technology Foundation of Hebei Agricultural University(Grant No.LG201804);Research Project for Self-cultivating Talents of Hebei Agricultural University(Grant No.PY201810)。; Imbalance in data distribution hinders the learning performance of classifiers.To solve this problem,a popular type of methods is based on sampling(including oversampling for minority class and undersampling for major...; 关键词：imbalance classification important sampling active learning OVERSAMPLING UNDERSAMPLING

How much information is lost when sampling driving behavior data?Indicators to quantify the extent of information loss: 《Journal of Intelligent and Connected Vehicles》2020年第1期17-29,共13页Jun Liu Asad Khattak Lee Han Quan Yuan; Purpose–Individuals’driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems.The incoming data can be sampled at rates ranging from one Hertz(or e...; 关键词：Driver behaviours and assistance Sensor data processing Information loss Instantaneous driving decisions Sampling rate UNDERSAMPLING

Scattering Center Modeling Using Adaptive Segmental Compressive Sampling: 《Journal of Beijing Institute of Technology》2017年第4期484-493,共10页Qifeng Li Kunyi Guo Jiaxin Wang Xinqing Sheng Tianshu Liu; Supported by the National Natural Science Foundation of China(61421001,61471041,61671059); In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation（ TFR） with aspect undersampling,an approach using adaptive segmental compressive sampling according to the asp...; 关键词：scattering center UNDERSAMPLING compressive sensing time-frequency representation parameter estimation

Sub-Rayleigh imaging via undersampling scanning based on sparsity constraints: 《Chinese Physics B》2017年第2期218-222,共5页Chang-Bin Xue Xu-Ri Yao Wen-Kai Yu Xiao-Yong Guo Long-Zhen Li Xue-Feng Liu Guang-Jie Zhai Qing Zhao; Project supported by the National Natural Science Foundation of China(Grant Nos.61605218 and 61601442);the National Defense Science and Technology Innovation Foundation of the Chinese Academy of Sciences(Grant No.CXJJ-16S047);the National Major Scientific Instruments Development Project of China(Grant No.2013YQ030595); We demonstrate that, by undersampling scanning object with a reconstruction algorithm related to compressed sensing, an image with the resolution exceeding the finest resolution defined by the numerical aperture of th...; 关键词：super-resolution image reconstruction techniques

A KNN Undersampling Approach for Data Balancing被引量：4: 《Journal of Intelligent Learning Systems and Applications》2015年第4期104-116,共13页Marcelo Beckmann Nelson F. F. Ebecken Beatriz S. L. Pires de Lima; In supervised learning, the imbalanced number of instances among the classes in a dataset can make the algorithms to classify one instance from the minority class as one from the majority class. With the aim to solve ...; 关键词：MACHINE LEARNING CLASS Overlaping Imbalanced Datases

Bernoulli-based random undersampling schemes for 2D seismic data regularization被引量：3: 《Applied Geophysics》2014年第3期321-330,351,352,共12页蔡瑞赵群佘德平杨丽曹辉杨勤勇; financially supported by The 2011 Prospective Research Project of SINOPEC(P11096); Seismic data regularization is an important preprocessing step in seismic signal processing. Traditional seismic acquisition methods follow the Shannon–Nyquist sampling theorem, whereas compressive sensing（CS） prov...; 关键词：Seismic data regularization compressive sensing Bernoulli distribution sparse transform UNDERSAMPLING 1-norm reconstruction algorithm.

An undersampling 14-bit cyclic ADC with over 100-dB SFDR: 《Journal of Semiconductors》2010年第2期64-69,共6页李玮韬李福乐郭丹丹张春王志华; supported by the National High Technology Research and Development Program of China(No.2006AA04A109); A high linearity,undersampling 14-bit 357 kSps cyclic analog-to-digital convert（ADC） is designed for a radio frequency identification transceiver system.The passive capacitor error-average（PCEA） technique is adopt...; 关键词：cyclic ADC high linearity UNDERSAMPLING improved passive capacitor error-average sampling network opamp sharing

Radial Basis Function Neural Network Based Super- Resolution Restoration for an Undersampled Image被引量：1: 《Journal of Beijing Institute of Technology》2004年第2期135-138,共4页苏秉华金伟其牛丽红; SponsoredbyFundforResearchonDoctoralProgramsinInstitutionsofHigherLearning ( 2 0 0 2 0 0 70 0 6)andBasicResearchFundofBIT (BIT UBF 2 0 0 3 0 1F2 0 ); To achieve restoration of high frequency information for an undersampled and degraded low-resolution image, a nonlinear and real-time processing method-the radial basis function (RBF) neural network based super-resolu...; 关键词：SUPER-RESOLUTION image restoration image processing neural networks UNDERSAMPLING

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