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  • Open Access


    Dealing with Imbalanced Dataset Leveraging Boundary Samples Discovered by Support Vector Data Description

    Zhengbo Luo1, Hamïd Parvïn2,3,4,*, Harish Garg5, Sultan Noman Qasem6,7, Kim-Hung Pho8, Zulkefli Mansor9

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2691-2708, 2021, DOI:10.32604/cmc.2021.012547

    Abstract These days, imbalanced datasets, denoted throughout the paper by ID, (a dataset that contains some (usually two) classes where one contains considerably smaller number of samples than the other(s)) emerge in many real world problems (like health care systems or disease diagnosis systems, anomaly detection, fraud detection, stream based malware detection systems, and so on) and these datasets cause some problems (like under-training of minority class(es) and over-training of majority class(es), bias towards majority class(es), and so on) in classification process and application. Therefore, these datasets take the focus of many researchers in any science… More >

  • Open Access


    Study for Multi-Resources Spatial Data Fusion Methods in Big Data Environment

    Zhiquan Huanga,b, Yu Fua, Fuchu Daia

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 29-34, 2018, DOI:10.1080/10798587.2016.1267237

    Abstract The rapid development and extensive application of geographic information system (GIS) and the advent of the age of big data bring about the generation of multi-resources spatial data, which makes data integration and fusion share more difficult due to the differences on data source, data accuracy and data modal. Meanwhile, study for multi-resources spatial data fusion methods has an important practical significance for reducing the production cost of geographic data, accelerating the updating speed of existing geographical information and improving the quality of GIS big data. To expound the formation and developing trends of multi-resources More >

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