Machine Learning and Data Mining in Pattern Recognition

Table of Contents

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   Book Overview
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   Chapter 1 Greedy Graph Edit Distance
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   Chapter 2 Learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation
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   Chapter 3 Seizure Prediction by Graph Mining, Transfer Learning, and Transformation Learning
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   Chapter 4 Local and Global Genetic Fuzzy Pattern Classifiers
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   Chapter 5 IKLTSA: An Incremental Kernel LTSA Method
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   Chapter 6 SentiSAIL: Sentiment Analysis in English, German and Russian
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   Chapter 7 Sentiment Analysis for Government: An Optimized Approach
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   Chapter 8 A Novel Algorithm for the Integration of the Imputation of Missing Values and Clustering
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    Chapter 9 Improving the Algorithm for Mapping of OWL to Relational Database Schema
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    Chapter 10 Robust Principal Component Analysis of Data with Missing Values
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    Chapter 11 Efficient Mining of High-Utility Sequential Rules
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    Chapter 12 MOGACAR: A Method for Filtering Interesting Classification Association Rules
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    Chapter 13 Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders
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    Chapter 14 Hybrid Approach for Inductive Semi Supervised Learning using Label Propagation and Support Vector Machine
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    Chapter 15 Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce
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    Chapter 16 Aggregation-Aware Compression of Probabilistic Streaming Time Series
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    Chapter 17 Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF)
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    Chapter 18 On Bicluster Aggregation and its Benefits for Enumerative Solutions
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    Chapter 19 Semi-Supervised Stream Clustering Using Labeled Data Points
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    Chapter 20 Avalanche: A Hierarchical, Divisive Clustering Algorithm
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    Chapter 21 Author Attribution of Email Messages Using Parse-Tree Features
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    Chapter 22 Robust Principal Component Analysis of Data with Missing Values
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    Chapter 23 Offline Writer Identification in Tamil Using Bagged Classification Trees
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    Chapter 24 Data Analysis for Courses Registration
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    Chapter 25 Learning the Relationship Between Corporate Governance and Company Performance Using Data Mining
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    Chapter 26 A Bayesian Approach to Sparse Learning-to-Rank for Search Engine Optimization
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    Chapter 27 Data Driven Geometry for Learning
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    Chapter 28 Mining Educational Data to Predict Students’ Academic Performance
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    Chapter 29 Patient-Specific Modeling of Medical Data
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    Chapter 30 A Bayesian Approach to Sparse Cox Regression in High-Dimentional Survival Analysis
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    Chapter 31 Automatic Cell Tracking and Kinetic Feature Description of Cell Paths for Image Mining