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

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Title -- Preface -- Organization -- Table of Contents -- Classification and Decision Theory -- Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier -- Introduction -- Maximum a Posteriori-Based Classifier -- Proposed Method -- Linear Model and Training Method -- A Unified Characterization of LSR and SVM -- A New Classifier -- Construction of GQCM Classifier -- Experiments -- Experiment Using Artificial Samples -- Performance with UCI Data Sets -- Discussion -- Conclusions and Future Work -- References -- Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification -- Introduction -- Related Work -- Hubness-Weighted kNN -- Fuzzy Nearest Neighbor Algorithm -- Proposed Hubness-Based Fuzzy Measures -- Experimental Evaluation -- UCI Data Sets -- ImageNet Data -- Conclusions and Future Work -- References -- Decisions: Algebra and Implementation -- Introduction -- Decision Algebra -- Decision Functions -- Learning and Deciding -- Auxiliary Decision Function Operations -- Decision Lattices -- The ``More Accurate'' Relations -- Approximating Decision Functions -- Experiments -- Implementation Details -- Decision Graph Sizes -- k-Approximated Decision Graphs -- Related Work -- Conclusions and Future Work -- References -- Smoothing Multinomial Naïve Bayes in the Presence of Imbalance -- Introduction -- Related Work -- Random OverSampling Expected Smoothing -- ROSE Smoothing Background -- ROSE Smoothing Approach -- Experiments -- Experiment 1: Standard Datasets -- Experiment 2: Class Prior Controlled Data Sets -- Conclusion -- References -- ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves -- Introduction -- Preliminaries and Related Work -- Computing Average Test Cost in Decision Tree and SVM -- Cost Efficient SVM -- Cost Efficient Decision Trees

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