Discovery Science

Table of Contents

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   Book Overview
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   Chapter 1 Exceptional Preferences Mining
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   Chapter 2 Local Subgroup Discovery for Eliciting and Understanding New Structure-Odor Relationships
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   Chapter 3 InterSet: Interactive Redescription Set Exploration
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   Chapter 4 Expect the Unexpected – On the Significance of Subgroups
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   Chapter 5 Min-Hashing for Probabilistic Frequent Subtree Feature Spaces
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   Chapter 6 STIFE: A Framework for Feature-Based Classification of Sequences of Temporal Intervals
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   Chapter 7 Approximating Numeric Role Fillers via Predictive Clustering Trees for Knowledge Base Enrichment in the Web of Data
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   Chapter 8 Option Predictive Clustering Trees for Multi-target Regression
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    Chapter 9 HSIM: A Supervised Imputation Method for Hierarchical Classification Scenario
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    Chapter 10 Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype
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    Chapter 11 Predicting Bug-Fix Time: Using Standard Versus Topic-Based Text Categorization Techniques
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    Chapter 12 Predicting Wildfires
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    Chapter 13 Recognizing Family, Genus, and Species of Anuran Using a Hierarchical Classification Approach
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    Chapter 14 Evolution Analysis of Call Ego-Networks
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    Chapter 15 Ensemble Diversity in Evolving Data Streams
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    Chapter 16 Learning Ensembles of Process-Based Models by Bagging of Random Library Samples
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    Chapter 17 Early Random Shapelet Forest
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    Chapter 18 Shorter Rules Are Better, Aren’t They?
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    Chapter 19 Exploiting Spatial Correlation of Spectral Signature for Training Data Selection in Hyperspectral Image Classification
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    Chapter 20 A Comparison of Different Data Transformation Approaches in the Feature Ranking Context
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    Chapter 21 On Selection Bias with Imbalanced Classes
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    Chapter 22 A Framework for Classification in Data Streams Using Multi-strategy Learning
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    Chapter 23 Anomaly Detection in Networks with Temporal Information
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    Chapter 24 Accelerating Computation of Distance Based Centrality Measures for Spatial Networks
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    Chapter 25 A Semi-supervised Approach to Measuring User Privacy in Online Social Networks
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    Chapter 26 On Using Temporal Networks to Analyze User Preferences Dynamics
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    Chapter 27 Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning
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    Chapter 28 Unsupervised Anomaly Detection in Noisy Business Process Event Logs Using Denoising Autoencoders
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    Chapter 29 DeepRED – Rule Extraction from Deep Neural Networks
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    Chapter 30 Ligand Affinity Prediction with Multi-pattern Kernels