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    SDM
    2008
    SIAM
    158views Data Mining» more  SDM 2008»
    Similarity Measures for Categorical Data: A Comparative Evaluation
    13 years 6 months ago
    Similarity Measures for Categorical Data: A Comparative Evaluation
    Download  www-users.cs.umn.edu
    Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relative...
    Shyam Boriah, Varun Chandola, Vipin Kumar
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    SDM
    2008
    SIAM
    133views Data Mining» more  SDM 2008»
    A RELIEF Based Feature Extraction Algorithm
    13 years 6 months ago
    A RELIEF Based Feature Extraction Algorithm
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    RELIEF is considered one of the most successful algorithms for assessing the quality of features due to its simplicity and effectiveness. It has been recently proved that RELIEF i...
    Yijun Sun, Dapeng Wu
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    SDM
    2008
    SIAM
    123views Data Mining» more  SDM 2008»
    Constrained Co-clustering of Gene Expression Data
    13 years 6 months ago
    Constrained Co-clustering of Gene Expression Data
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    In many applications, the expert interpretation of coclustering is easier than for mono-dimensional clustering. Co-clustering aims at computing a bi-partition that is a collection...
    Ruggero G. Pensa, Jean-François Boulicaut
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    SDM
    2008
    SIAM
    140views Data Mining» more  SDM 2008»
    Large-Scale Many-Class Learning
    13 years 6 months ago
    Large-Scale Many-Class Learning
    Download  www.personal.psu.edu
    In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
    Omid Madani, Michael Connor
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    SDM
    2008
    SIAM
    139views Data Mining» more  SDM 2008»
    Simultaneous Unsupervised Learning of Disparate Clusterings
    13 years 6 months ago
    Simultaneous Unsupervised Learning of Disparate Clusterings
    Download  www.cs.utexas.edu
    Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
    Prateek Jain, Raghu Meka, Inderjit S. Dhillon
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    SDM
    2008
    SIAM
    139views Data Mining» more  SDM 2008»
    Semi-Supervised Learning Based on Semiparametric Regularization
    13 years 6 months ago
    Semi-Supervised Learning Based on Semiparametric Regularization
    Download  www.fortune.binghamton.edu
    Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
    Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
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    SDM
    2008
    SIAM
    138views Data Mining» more  SDM 2008»
    Clustering from Constraint Graphs
    13 years 6 months ago
    Clustering from Constraint Graphs
    Download  www.cs.cmu.edu
    In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
    Ari Freund, Dan Pelleg, Yossi Richter
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    SDM
    2008
    SIAM
    125views Data Mining» more  SDM 2008»
    Mining and Ranking Generators of Sequential Patterns
    13 years 6 months ago
    Mining and Ranking Generators of Sequential Patterns
    Download  www.comp.nus.edu.sg
    Sequential pattern mining first proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements...
    David Lo, Siau-Cheng Khoo, Jinyan Li
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    SDM
    2008
    SIAM
    197views Data Mining» more  SDM 2008»
    A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees
    13 years 6 months ago
    A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees
    Download  cui.unige.ch
    Decision trees are among the most popular pattern types in data mining due to their intuitive representation. However, little attention has been given on the definition of measure...
    Irene Ntoutsi, Alexandros Kalousis, Yannis Theodor...
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    SDM
    2008
    SIAM
    161views Data Mining» more  SDM 2008»
    Efficient Maximum Margin Clustering via Cutting Plane Algorithm
    13 years 6 months ago
    Efficient Maximum Margin Clustering via Cutting Plane Algorithm
    Download  siam.org
    Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
    Bin Zhao, Fei Wang, Changshui Zhang
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