Browsing by Author "Qin, Zhenxing"

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Browsing by Author "Qin, Zhenxing"

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  • Zhang, Chengqi; Qin, Zhenxing; Yan, Xiaowei (IEEE Computer Society, 2005)
  • Huang, Qi Rong; Qin, Zhenxing; Zhang, Shichao; Chow, Chin (The American Academy of Sleep Medicine, 2008)
    Objectives: Obstructive sleep apnea often results in a wide range of comorbid conditions. Although some conditions have been clearly identified as comorbid, a full clinical pattern of associated diseases has not been ...
  • Qin, Zhenxing; Zhang, Chengqi; Wang, Tao; Zhang, Shichao (Springer-Verlag, 2010)
    Cost-sensitive classification is one of mainstream research topics in data mining and machine learning that induces models from data with unbalance class distributions and impacts by quantifying and tackling the unbalance. ...
  • Wang, Tao; Qin, Zhenxing; Zhang, Shichao; Zhang, Chengqi (Elsevier, 2012)
    It is an actual and challenging issue to learn cost-sensitive models from those datasets that are with few labeled data and plentiful unlabeled data, because some time labeled data are very difficult, time consuming and/or ...
  • Qin, Zhenxing; Wang, Tao; Zhang, Chengqi; Zhang, Shichao (Springer, 2013)
    Cost-sensitive learning algorithms are typically motivated by imbalance data in clinical diagnosis that contains skewed class distribution. While other popular classification methods have been improved against imbalance ...
  • Qin, Zhenxing; Zhang, Shichao; Zhang, Chengqi (Springer, 2004)
    How to minimize misclassification errors has been the main focus of Inductive learning techniques, such as CART and C4.5. However, misclassification error is not the only error in classification problem. Recently, researchers ...
  • Qin, Zhenxing; Zhang, Shichao; Liu, Li; Wang, Tao (IEEE Computer Society, 2008)
    In many real world data mining and classification tasks, we face with the problem of high cost in making training data sets. In addition, in many domains, different misclassification errors involve different costs. These ...
  • Qin, Zhenxing; Zhang, Chengqi; Xie, Xuehui; Zhang, Shichao (Springer-Verlag Berlin, 2005)
    Previous work considering both test and misclassification costs rely on the assumption that the test cost and the misclassification cost must be defined on the same cost scale. However, it can be difficult to define the ...
  • Wang, Tao; Qin, Zhenxing; Jin, Zhi; Zhang, Shichao (Elsevier Ltd, 2010)
    Cost-sensitive learning algorithms are typically designed for minimizing the total cost when multiple costs are taken into account. Like other learning algorithms, cost-sensitive learning algorithms must face a significant ...
  • Qin, Zhenxing; Su, Gao-Li; Zhang, Ji-Wen; Ouyang, Ying; Yu, Qiang; Li, Jianchun (Elsevier Science Bv, 2010)
    Water vapor flux and carbon dioxide (CO2) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation ...
  • Zhang, Chengqi; Zhang, Shichao; Yan, Xiaowei; Qin, Zhenxing (Nanyang Technological University, 2002)
  • Qin, Zhenxing; Wang, Tao; Zhang, Shichao (IEEE, 2010)
    This paper studies an actual and new setting of cost-sensitive learning, i.e., combining test data with medical history under multiple-scale cost constraints. With a new cost structure, an attribute selection strategy is ...
  • Yan, Xiaowei; Zhang, Chengqi; Zhang, Shichao; Qin, Zhenxing (Idea Group Publishing, 2003)
    Prevailing information retrieval methods are based on either term similarity or latent semantics. Terms are considered independently. This paper presents a new strategy for information retrieval, i.e., indexing by conditional ...
  • Zhang, Chengqi; Zhang, Shichao; Yan, Xiaowei; Qin, Zhenxing (Nanyang Technological University, 2002)
  • Qin, Zhenxing; Liu, Li; Zhang, Shichao (Springer, 2004)
    As the Web has become an important channel of information floods, users have had difficulty on identifying what they really want from huge amounts of rubbish-like information provided by the Web search engines when utilizing ...
  • Zhang, Shichao; Qin, Zhenxing; Ling, Charles; Sheng, Shengli (IEEE Computer Soc, 2005)
    Many real-world data sets for machine learning and data mining contain missing values and much previous research regards it as a problem and attempts to impute missing values before training and testing. In this paper, we ...
  • Qin, Zhenxing; Zhang, Shichao; Zhang, Chengqi (IOS Press, 2006)
  • Zhang, Shichao; Zhang, Chengqi; Qin, Zhenxing (Grace Publications, 2003)
    Recently, many temporal query languages, such as TCAL and TQuel have been proposed for temporal databases. However, there are still some limitations such as the inadequacy on operating data with temporal elements and ...
  • Yang, Yiming; Yang, Qiang; Lu, Wei; Pan, Jialin; Pan, Rong; Lu, Chenhui; Li, Lei; Qin, Zhenxing (Springer, 2005)
    We develop an innovative data preprocessing algorithm for classifying customers using unbalanced time series data. This problem is directly motivated by an application whose aim is to uncover the customers? churning behavior ...