Machine Learning and Data Mining in Pattern Recognition - Info and Reading Options

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Title -- Preface -- Table of Contents -- Theory -- Bayesian Approach to the Concept Drift in the Pattern Recognition Problems -- Introduction -- Bayesian Approach to the Problem of Concept Drift for the Pattern Recognition Problem -- Dynamic Programming Procedure for the Estimation of the Decision Rule Parameters under Concept Drift -- Experimental Evaluation -- ``Ground-Truth'' Experiments -- Case Study: ``Spam'' E-Mail Problem -- Conclusion -- References -- Transductive Relational Classification in the Co-training Paradigm -- Introduction -- Related Work -- Transductive Learning -- Multi-view Learning -- Co-training -- The CoTReC Method -- Constructing Multi-views from Relational Data -- Reliability Measures -- Computing Reliability Thresholds -- Implementation Considerations -- Experiments -- Datasets -- Experimental Results -- Conclusions -- References -- Generalized Nonlinear Classification Model Based on Cross-Oriented Choquet Integral -- Introduction -- Signed Efficiency Measure, Choquet Integral, and Classification -- Signed Efficiency Measure -- Choquet Integral -- Classification by Choquet Integral Projections -- Generalized Classification Model by Cross-Oriented Projection -- Algorithms -- Experiments -- Simulation on Artificial Data -- Simulation on Real Data -- Conclusions -- References -- A General Lp-norm Support Vector Machine via Mixed 0-1 Programming -- Introduction -- A General Lp-norm Support Vector Machine -- Optimizing General Lp-norm Support Vector Machine -- Experiment -- Experimental Settings -- Experimental Results -- Conclusions -- References -- Reduction of Distance Computations in Selection of Pivot Elements for Balanced GHT Structure -- Introduction -- Distance Matrices -- Selection of Pivot Elements -- Improvements of the Local Optimization Method -- Interval Model of Distance Calculations -- Conclusions

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