Complete List » Classification

Publications Related to Classification

  1. AREM: A Novel Associative Regression Model Based on the EM Algorithm.

    Zhonghua Jiang and George Karypis. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2013.

  1. Multi-view learning via probabilistic latent semantic analysis .

    Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, and Zhongzhi Shi. Information Sciences, 199; pp. 20-30, 2012.

  1. The Set Classification Problem and Solution Methods.

    Xia Ning and George Karypis. SIAM Data Mining, pp. 847-858, 2009.

  1. Within-network classification using local structure similarity.

    Christian Desrosiers and George Karypis. ECML-PKDD, pp. 260-275, 2009.

  1. TOPTMH: Topology Predictor for Transmembrane a-Helices.

    Rezwan Ahmed, Huzefa Rangwala, and George Karypis. ECML-PKDD, 2008.

  1. Comparison of Descriptor Spaces for Chemical Compound Retrieval and Classification.

    Nikil Wale, Ian Watson, and George Karypis. Knowledge and Information Systems, 2007.

  1. fRMSDPred: Predicting local rmsd between structural fragments using sequence information.

    Huzefa Rangwala and George Karypis. Computational Systems Biology (CSB), pp. 311-322, 2007.

  1. On Mining Instance-Centric Classification Rules.

    Jianyong Wang and George Karypis. IEEE Transactions on Knowledge and Data Enigneering, 2006.

  1. Building Multiclass Classifiers for Remote Homology Detection and Fold Recognition.

    Huzefa Rangwala and George Karypis. BMC Bioinformatics, Jan 15;23(2):e17-23., 2006.

  1. YASSPP: Better Kernels and Coding Schemes Lead to Improvements in SVM-basedSecondary Structure Prediction.

    George Karypis. PROTEINS: Structure, Function, and Bioinformatics, 2006.

  1. HARMONY: Efficiently Mining the Best Rules for Classification.

    Jianyong Wang and George Karypis. SIAM International Conference on Data Mining, pp. 205--216, 2005.

  1. Topic-Driven Clustering for Document Datasets.

    Ying Zhao and George Karypis. SIAM International Conference on Data Mining, pp. 358-369, 2005.