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    DMIN   2007
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    2007
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    Generative Oversampling for Mining Imbalanced Datasets
    14 years 1 months ago
    Generative Oversampling for Mining Imbalanced Datasets
    Download  www.ideal.ece.utexas.edu
    — One way to handle data mining problems where class prior probabilities and/or misclassification costs between classes are highly unequal is to resample the data until a new, d...
    Alexander Liu, Joydeep Ghosh, Cheryl Martin
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    1Download preprint from source226
    Generative Oversampling for Mining Imbalanced Datasets
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    2Download preprint from source214
    A Fast KNN Algorithm Based on Simulated Annealing
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    3Download preprint from source203
    Evaluation of Feature Selection Techniques for Analysis of Functional MRI and EEG
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    4Download preprint from source186
    Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
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    5Download preprint from source183
    Crawling Attacks Against Web-based Recommender Systems
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    6Download preprint from source168
    On Clustering Users' Behaviors in Video Sessions
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    7Download preprint from source161
    Efficient Summarization Based On Categorized Keywords
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    8Download preprint from source158
    Mining Frequent Itemsets Using Re-Usable Data Structure
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    9Download preprint from source110
    Mining for Structural Anomalies in Graph-based Data
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    10Download preprint from source91
    Instance Ranking using Ensemble Spread
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    11Download preprint from source90
    On Minimal Infrequent Itemset Mining
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    12Download preprint from source85
    A Clustering Approach for Achieving Data Privacy
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    13Download preprint from source79
    The Internet Democracy: A Predictive Model Based on Web Text Mining
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    14Download preprint from source76
    Towards Average Case Analysis of Itemset Mining
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