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Encyclopedia of Machine Learning

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Cover of 'Encyclopedia of Machine Learning'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Abduction
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    Chapter 2 Absolute Error Loss
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    Chapter 3 Accuracy
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    Chapter 4 ACO
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    Chapter 5 Actions
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    Chapter 6 Active Learning
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    Chapter 7 Active Learning Theory
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    Chapter 8 Adaboost
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    Chapter 9 Adaptive Control Processes
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    Chapter 10 Adaptive Real-Time Dynamic Programming
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    Chapter 11 Adaptive Resonance Theory
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    Chapter 12 Adaptive System
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    Chapter 13 Agent
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    Chapter 14 Agent-Based Computational Models
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    Chapter 15 Agent-Based Modeling and Simulation
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    Chapter 16 Agent-Based Simulation Models
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    Chapter 17 AIS
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    Chapter 18 Algorithm Evaluation
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    Chapter 19 Analogical Reasoning
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    Chapter 20 Analysis of Text
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    Chapter 21 Analytical Learning
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    Chapter 22 Ant Colony Optimization
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    Chapter 23 Anytime Algorithm
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    Chapter 24 AODE
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    Chapter 25 Apprenticeship Learning
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    Chapter 26 Approximate Dynamic Programming
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    Chapter 27 Apriori Algorithm
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    Chapter 28 Area Under Curve
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    Chapter 29 AQ
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    Chapter 30 ARL
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    Chapter 31 Encyclopedia of Machine Learning
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    Chapter 32 ARTDP
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    Chapter 33 Artificial Immune Systems
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    Chapter 34 Encyclopedia of Machine Learning
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    Chapter 35 Artificial Neural Networks
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    Chapter 36 Artificial Societies
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    Chapter 37 Assertion
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    Chapter 38 Association Rule
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    Chapter 39 Associative Bandit Problem
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    Chapter 40 Associative Reinforcement Learning
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    Chapter 41 Attribute
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    Chapter 42 Attribute Selection
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    Chapter 43 Attribute-Value Learning
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    Chapter 44 AUC
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    Chapter 45 Autonomous Helicopter Flight Using Reinforcement Learning
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    Chapter 46 Average-Cost Neuro-Dynamic Programming
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    Chapter 47 Average-Cost Optimization
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    Chapter 48 Averaged One-Dependence Estimators
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    Chapter 49 Average-Reward Reinforcement Learning
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    Chapter 50 Backprop
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    Chapter 51 Backpropagation
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    Chapter 52 Bagging
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    Chapter 53 Bake-Off
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    Chapter 54 Bandit Problem with Side Information
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    Chapter 55 Bandit Problem with Side Observations
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    Chapter 56 Basic Lemma
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    Chapter 57 Basket Analysis
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    Chapter 58 Batch Learning
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    Chapter 59 Baum-Welch Algorithm
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    Chapter 60 Bayes Adaptive Markov Decision Processes
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    Chapter 61 Bayes Net
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    Chapter 62 Bayes Rule
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    Chapter 63 Bayesian Methods
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    Chapter 64 Bayesian Model Averaging
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    Chapter 65 Bayesian Network
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    Chapter 66 Bayesian Nonparametric Models
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    Chapter 67 Bayesian Reinforcement Learning
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    Chapter 68 Encyclopedia of Machine Learning
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    Chapter 69 Encyclopedia of Machine Learning
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    Chapter 70 Belief State Markov Decision Processes
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    Chapter 71 Bellman Equation
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    Chapter 72 Bias
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    Chapter 73 Bias Specification Language
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    Chapter 74 Bias Variance Decomposition
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    Chapter 75 Bias-Variance Trade-offs: Novel Applications
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    Chapter 76 Bias-Variance Trade-offs
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    Chapter 77 Bias-Variance-Covariance Decomposition
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    Chapter 78 Bilingual Lexicon Extraction
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    Chapter 79 Binning
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    Chapter 80 Biological Learning: Synaptic Plasticity, Hebb Rule and Spike TimingDependent Plasticity
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    Chapter 81 Biomedical Informatics
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    Chapter 82 Blog Mining
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    Chapter 83 Boltzmann Machines
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    Chapter 84 Boosting
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    Chapter 85 Bottom Clause
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    Chapter 86 Bounded Differences Inequality
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    Chapter 87 BP
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    Chapter 88 Breakeven Point
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    Chapter 89 C4.5
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    Chapter 90 Cannot-Link Constraint
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    Chapter 91 Candidate-Elimination Algorithm
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    Chapter 92 Cascade-Correlation
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    Chapter 93 CART
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    Chapter 94 Cascor
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    Chapter 95 Case
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    Chapter 96 Case-Based Learning
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    Chapter 97 Case-Based Reasoning
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    Chapter 98 Categorical Attribute
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    Chapter 99 Categorical Data Clustering
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    Chapter 100 Categorization
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    Chapter 101 Category
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    Chapter 102 Causal Discovery
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    Chapter 103 Causality
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    Chapter 104 CBR
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    Chapter 105 CC
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    Chapter 106 Certainty Equivalence Principle
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    Chapter 107 Characteristic
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    Chapter 108 City Block Distance
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    Chapter 109 Class
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    Chapter 110 Class Imbalance Problem
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    Chapter 111 Classification
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    Chapter 112 Classification Algorithms
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    Chapter 113 Classification Learning
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    Chapter 114 Classification Tree
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    Chapter 115 Classifier Systems
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    Chapter 116 Clause
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    Chapter 117 Clause Learning
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    Chapter 118 Click-Through Rate (CTR)
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    Chapter 119 Clonal Selection
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    Chapter 120 Closest Point
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    Chapter 121 Cluster Editing
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    Chapter 122 Cluster Ensembles
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    Chapter 123 Cluster Optimization
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    Chapter 124 Clustering
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    Chapter 125 Clustering Aggregation
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    Chapter 126 Clustering Ensembles
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    Chapter 127 Clustering from Data Streams
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    Chapter 128 Clustering of Nonnumerical Data
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    Chapter 129 Clustering with Advice
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    Chapter 130 Clustering with Constraints
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    Chapter 131 Clustering with Qualitative Information
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    Chapter 132 Clustering with Side Information
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    Chapter 133 CN2
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    Chapter 134 Co-Training
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    Chapter 135 Encyclopedia of Machine Learning
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    Chapter 136 Coevolutionary Computation
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    Chapter 137 Coevolutionary Learning
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    Chapter 138 Collaborative Filtering
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    Chapter 139 Collection
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    Chapter 140 Collective Classification
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    Chapter 141 Commercial Email Filtering
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    Chapter 142 Committee Machines
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    Chapter 143 Community Detection
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    Chapter 144 Comparable Corpus
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    Chapter 145 Competitive Coevolution
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    Chapter 146 Competitive Learning
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    Chapter 147 Complex Adaptive System
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    Chapter 148 Complexity in Adaptive Systems
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    Chapter 149 Complexity of Inductive Inference
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    Chapter 150 Compositional Coevolution
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    Chapter 151 Computational Complexity of Learning
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    Chapter 152 Computational Discovery of Quantitative Laws
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    Chapter 153 Encyclopedia of Machine Learning
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    Chapter 154 Encyclopedia of Machine Learning
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    Chapter 155 Conditional Random Field
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    Chapter 156 Confirmation Theory
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    Chapter 157 Confusion Matrix
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    Chapter 158 Conjunctive Normal Form
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    Chapter 159 Connection Strength
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    Chapter 160 Connections Between Inductive Inference and Machine Learning
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    Chapter 161 Connectivity
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    Chapter 162 Consensus Clustering
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    Chapter 163 Constrained Clustering
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    Chapter 164 Constraint-Based Mining
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    Chapter 165 Constructive Induction
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    Chapter 166 Content Match
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    Chapter 167 Content-Based Filtering
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    Chapter 168 Content-Based Recommending
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    Chapter 169 Context-Sensitive Learning
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    Chapter 170 Contextual Advertising
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    Chapter 171 Continual Learning
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    Chapter 172 Continuous Attribute
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    Chapter 173 Contrast Set Mining
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    Chapter 174 Cooperative Coevolution
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    Chapter 175 Co-Reference Resolution
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    Chapter 176 Correlation Clustering
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    Chapter 177 Correlation-Based Learning
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    Chapter 178 Cost
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    Chapter 179 Cost Function
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    Chapter 180 Cost-Sensitive Classification
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    Chapter 181 Cost-Sensitive Learning
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    Chapter 182 Cost-to-Go Function Approximation
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    Chapter 183 Covariance Matrix
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    Chapter 184 Covering Algorithm
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    Chapter 185 Encyclopedia of Machine Learning
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    Chapter 186 Cross-Language Document Categorization
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    Chapter 187 Cross-Language Information Retrieval
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    Chapter 188 Cross-Language Question Answering
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    Chapter 189 Cross-Lingual Text Mining
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    Chapter 190 Cross-Validation
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    Chapter 191 Cumulative Learning
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    Chapter 192 Curse of Dimensionality
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    Chapter 193 Data Mining On Text
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    Chapter 194 Data Preparation
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    Chapter 195 Data Preprocessing
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    Chapter 196 Data Set
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    Chapter 197 DBN
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    Chapter 198 Decision Epoch
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    Chapter 199 Decision List
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    Chapter 200 Decision Lists and Decision Trees
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    Chapter 201 Decision Rule
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    Chapter 202 Decision Stump
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    Chapter 203 Decision Threshold
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    Chapter 204 Decision Tree
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    Chapter 205 Decision Trees For Regression
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    Chapter 206 Deductive Learning
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    Chapter 207 Deduplication
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    Chapter 208 Deep Belief Nets
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    Chapter 209 Deep Belief Networks
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    Chapter 210 Encyclopedia of Machine Learning
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    Chapter 211 Density-Based Clustering
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    Chapter 212 Dependency Directed Backtracking
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    Chapter 213 Detail
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    Chapter 214 Deterministic Decision Rule
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    Chapter 215 Digraphs
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    Chapter 216 Dimensionality Reduction
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    Chapter 217 Dimensionality Reduction on Text via Feature Selection
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    Chapter 218 Directed Graphs
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    Chapter 219 Dirichlet Process
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    Chapter 220 Discrete Attribute
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    Chapter 221 Discretization
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    Chapter 222 Discriminative Learning
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    Chapter 223 Disjunctive Normal Form
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    Chapter 224 Distance
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    Chapter 225 Distance Functions
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    Chapter 226 Distance Measures
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    Chapter 227 Distance Metrics
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    Chapter 228 Distribution-Free Learning
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    Chapter 229 Divide-and-Conquer Learning
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    Chapter 230 Document Classification
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    Chapter 231 Document Clustering
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    Chapter 232 Dual Control
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    Chapter 233 Duplicate Detection
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    Chapter 234 Dynamic Bayesian Network
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    Chapter 235 Dynamic Decision Networks
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    Chapter 236 Dynamic Memory Model
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    Chapter 237 Dynamic Programming
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    Chapter 238 Dynamic Programming For Relational Domains
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    Chapter 239 Dynamic Systems
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    Chapter 240 EBL
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    Chapter 241 Echo State Network
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    Chapter 242 ECOC
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    Chapter 282 Encyclopedia of Machine Learning
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    Chapter 327 Encyclopedia of Machine Learning
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    Chapter 334 Encyclopedia of Machine Learning
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    Chapter 353 Encyclopedia of Machine Learning
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    Chapter 363 Encyclopedia of Machine Learning
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    Chapter 388 Encyclopedia of Machine Learning
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    Chapter 488 Locally Weighted Regression for Control
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    Chapter 511 Encyclopedia of Machine Learning
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    Chapter 594 Encyclopedia of Machine Learning
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    Chapter 630 Particle Swarm Optimization
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    Chapter 678 Encyclopedia of Machine Learning
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    Chapter 885 1-Norm Distance
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    Chapter 886 Bootstrap Sampling
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    Chapter 892 Average-Payoff Reinforcement Learning
Attention for Chapter 102: Causal Discovery
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Chapter title
Causal Discovery
Chapter number 102
Book title
Encyclopedia of Machine Learning
Published by
Springer US, January 2011
DOI 10.1007/978-0-387-30164-8_102
Book ISBNs
978-0-387-30768-8, 978-0-387-30164-8
Authors

Shultz, Thomas R., Fahlman, Scott E., Craw, Susan, Andritsos, Periklis, Tsaparas, Panayiotis, Silva, Ricardo, Drummond, Chris, Ling, Charles X., Sheng, Victor S., Lanzi, Pier Luca, Gama, João, Wiegand, R. Paul, Sen, Prithviraj, Namata, Galileo, Bilgic, Mustafa, Getoor, Lise, He, Jun, Jain, Sanjay, Stephan, Frank, Sammut, Claude, Harries, Michael, Ting, Kai Ming, Pfahringer, Bernhard, Case, John, Wagstaff, Kiri L., Nijssen, Siegfried, Wirth, Anthony, Zhang, Xinhua, Cancedda, Nicola, Renders, Jean-Michel, Michelucci, Pietro, Oblinger, Daniel, Keogh, Eamonn, Mueen, Abdullah, Thomas R. Shultz, Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, Charles X. Ling, Victor S. Sheng, Pier Luca Lanzi, João Gama, R. Paul Wiegand, Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Jun He, Sanjay Jain, Frank Stephan, Claude Sammut, Michael Harries, Kai Ming Ting, Bernhard Pfahringer, John Case, Kiri L. Wagstaff, Siegfried Nijssen, Anthony Wirth, Xinhua Zhang, Nicola Cancedda, Jean-Michel Renders, Pietro Michelucci, Daniel Oblinger, Eamonn Keogh, Abdullah Mueen

Editors

Claude Sammut, Geoffrey I. Webb

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Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 100%
Readers by discipline Count As %
Mathematics 1 100%