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Encyclopedia of Machine Learning and Data Mining

Overview of attention for book
Encyclopedia of Machine Learning and Data Mining
Springer US

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Abduction
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    Chapter 3 Accuracy
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    Chapter 5 Actions
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    Chapter 6 Adaptive Resonance Theory
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    Chapter 7 Active Learning Theory
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    Chapter 10 Adaptive Real-Time Dynamic Programming
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    Chapter 13 Agent
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    Chapter 16 Autonomous Helicopter Flight Using Reinforcement Learning
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    Chapter 17 Average-Reward Reinforcement Learning
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    Chapter 18 Algorithm Evaluation
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    Chapter 21 Bayes’ Rule
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    Chapter 22 Ant Colony Optimization
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    Chapter 23 Anytime Algorithm
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    Chapter 27 Apriori Algorithm
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    Chapter 28 Bias-Variance Trade-Offs: Novel Applications
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    Chapter 30 Biomedical Informatics
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    Chapter 31 Boltzmann Machines
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    Chapter 33 Cascade Correlation
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    Chapter 34 Case-Based Reasoning
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    Chapter 35 Categorical Data Clustering
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    Chapter 36 Causality
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    Chapter 37 Assertion
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    Chapter 38 Association Rule
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    Chapter 40 Associative Reinforcement Learning
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    Chapter 41 Clustering from Data Streams
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    Chapter 43 Attribute-Value Learning
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    Chapter 44 Collective Classification
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    Chapter 45 Complexity in Adaptive Systems
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    Chapter 46 Complexity of Inductive Inference
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    Chapter 47 Computational Complexity of Learning
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    Chapter 48 Averaged One-Dependence Estimators
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    Chapter 50 Confusion Matrix
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    Chapter 51 Backpropagation
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    Chapter 52 Connections Between Inductive Inference and Machine Learning
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    Chapter 53 Bake-Off
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    Chapter 57 Covariance Matrix
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    Chapter 58 Batch Learning
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    Chapter 59 Baum-Welch Algorithm
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    Chapter 62 Data Preparation
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    Chapter 63 Bayesian Methods
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    Chapter 64 Decision List
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    Chapter 65 Decision Lists and Decision Trees
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    Chapter 66 Decision Tree
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    Chapter 67 Deep Belief Nets
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    Chapter 68 Beam Search
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    Chapter 69 Behavioral Cloning
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    Chapter 70 Density-Based Clustering
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    Chapter 71 Dimensionality Reduction
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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 Document Classification
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    Chapter 78 Bilingual Lexicon Extraction
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    Chapter 80 Biological Learning: Synaptic Plasticity, Hebb Rule and Spike Timing Dependent Plasticity
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    Chapter 84 Boosting
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    Chapter 91 Candidate-Elimination Algorithm
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    Chapter 98 Categorical Attribute
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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 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 121 Cluster Editing
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    Chapter 122 Cluster Ensembles
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    Chapter 146 Competitive Learning
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    Chapter 150 Compositional Coevolution
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    Chapter 153 Concept Drift
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    Chapter 154 Concept Learning
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    Chapter 155 Conditional Random Field
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    Chapter 156 Confirmation Theory
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    Chapter 158 Conjunctive Normal Form
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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 167 Content-Based Filtering
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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 176 Correlation Clustering
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    Chapter 178 Cost
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    Chapter 181 Cost-Sensitive Learning
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    Chapter 185 Credit Assignment
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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 196 Data Set
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    Chapter 197 DBN
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    Chapter 198 Decision Epoch
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    Chapter 201 Decision Rule
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    Chapter 203 Decision Threshold
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    Chapter 206 Deductive Learning
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    Chapter 210 Density Estimation
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    Chapter 213 Detail
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    Chapter 215 Digraphs
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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 275 Covering Algorithm
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    Chapter 285 Decision Stump
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    Chapter 303 Divide-and-Conquer Learning
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    Chapter 900 Classifier Calibration
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    Chapter 909 Deep Learning
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    Chapter 912 Active Learning
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    Chapter 914 Classification Rule
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    Chapter 915 Class Binarization
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    Chapter 916 Active Learning
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    Chapter 917 Adaboost
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    Chapter 918 Area Under Curve
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    Chapter 919 Artificial Immune Systems
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    Chapter 920 Artificial Life
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    Chapter 921 Artificial Neural Networks
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    Chapter 922 Artificial Societies
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    Chapter 923 Attribute
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    Chapter 925 Bagging
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    Chapter 926 Basket Analysis
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    Chapter 927 Bayesian Network
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    Chapter 928 Bayesian Nonparametric Models
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    Chapter 929 Bayesian Reinforcement Learning
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    Chapter 930 Bellman Equation
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    Chapter 932 Bias-Variance-Covariance Decomposition
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    Chapter 934 Blog Mining
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    Chapter 936 Bottom Clause
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    Chapter 937 Breakeven Point
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    Chapter 938 Cannot-Link Constraint
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    Chapter 940 Class
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    Chapter 941 Classifier Systems
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    Chapter 942 Clonal Selection
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    Chapter 943 Clustering
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    Chapter 944 Coevolutionary Learning
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    Chapter 945 Collaborative Filtering
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    Chapter 946 Comparable Corpus
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    Chapter 977 Bootstrap Sampling
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    Chapter 979 Data Enrichment
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    Chapter 10025 AUC
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    Chapter 100003 ACO
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    Chapter 100004 Adaptive Control Processes
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    Chapter 100005 Adaptive Learning
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    Chapter 100007 Agent-Based Computational Models
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    Chapter 100008 Agent-Based Modeling and Simulation
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    Chapter 100009 Agent-Based Simulation Models
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    Chapter 100010 AIS
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    Chapter 100012 Analogical Reasoning
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    Chapter 100013 Analysis of Text
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    Chapter 100015 Analytical Learning
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    Chapter 100016 AODE
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    Chapter 100017 Apprenticeship Learning
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    Chapter 100018 Approximate Dynamic Programming
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    Chapter 100019 Architecture
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    Chapter 100020 ARL
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    Chapter 100021 ARTDP
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    Chapter 100022 Assessment of Model Performance
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    Chapter 100023 Associative Bandit Problem
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    Chapter 100026 Authority Control
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    Chapter 100027 Average-Cost Neuro-Dynamic Programming
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    Chapter 100028 Average-Cost Optimization
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    Chapter 100029 Average-Payoff Reinforcement Learning
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    Chapter 100030 Backprop
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    Chapter 100031 Bandit Problem with Side Information
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    Chapter 100032 Bandit Problem with Side Observations
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    Chapter 100033 Basic Lemma
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    Chapter 100034 Bayes Adaptive Markov Decision Processes
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    Chapter 100035 Bayes Net
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    Chapter 100036 Bayes’ Theorem
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    Chapter 100038 Bayesian Model Averaging
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    Chapter 100039 Belief State Markov Decision Processes
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    Chapter 100040 Binning
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    Chapter 100041 Bounded Differences Inequality
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    Chapter 100042 BP
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    Chapter 100043 Cascor
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    Chapter 100044 Case
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    Chapter 100045 Case-Based Learning
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    Chapter 100046 Categorization
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    Chapter 100048 Category
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    Chapter 100049 Causal Discovery
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    Chapter 100050 CC
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    Chapter 100051 Certainty Equivalence Principle
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    Chapter 100052 Characteristic
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    Chapter 100053 Citation or Reference Matching (When Applied to Bibliographic Data)
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    Chapter 100054 City Block Distance
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    Chapter 100055 Classification Learning
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    Chapter 100056 Classification Tree
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    Chapter 100057 Closest Point
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    Chapter 100058 Cluster Initialization
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    Chapter 100059 Cluster Optimization
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    Chapter 100060 Clustering Aggregation
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    Chapter 100061 Clustering Ensembles
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    Chapter 100062 Clustering of Nonnumerical Data
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    Chapter 100063 Clustering with Advice
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    Chapter 100064 Clustering with Constraints
  199. Altmetric Badge
    Chapter 100065 Clustering with Qualitative Information
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    Chapter 100066 Clustering with Side Information
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    Chapter 100067 Coevolution
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    Chapter 100068 Coevolutionary Computation
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    Chapter 100069 Collection
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    Chapter 100070 Commercial Email Filtering
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    Chapter 100071 Committee Machines
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    Chapter 100072 Community Detection
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    Chapter 100073 Comparison Training
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    Chapter 100074 Competitive Coevolution
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    Chapter 100075 Complex Adaptive System
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    Chapter 100077 Computational Discovery of Quantitative Laws
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    Chapter 100078 Connection Strength
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    Chapter 100079 Connectivity
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    Chapter 100080 Constraint Classification
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    Chapter 100081 Content Match
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    Chapter 100082 Content-Based Recommending
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    Chapter 100083 Context-Sensitive Learning
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    Chapter 100084 Contextual Advertising
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    Chapter 100086 Cooperative Coevolution
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    Chapter 100087 Co-reference Resolution
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    Chapter 100089 Correlation-Based Learning
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    Chapter 100091 Cost Function
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    Chapter 100092 Cost-Sensitive Classification
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    Chapter 100093 Cost-to-Go Function Approximation
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    Chapter 100094 Co-training
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    Chapter 100096 Data Cleansing
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    Chapter 100097 Data Linkage
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    Chapter 100098 Data Matching
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    Chapter 100099 Data mining on Text
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    Chapter 100100 Data Preprocessing
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    Chapter 100101 Data Reconciliation
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    Chapter 100102 Data Wrangling
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    Chapter 100103 Decision Trees for Regression
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    Chapter 100105 Deduplication
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    Chapter 100106 Deduplication or Duplicate Detection (When Applied to One Database Only)
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    Chapter 100107 Deep Belief Networks
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    Chapter 100109 Dependency Directed Backtracking
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    Chapter 100110 Diagonal Matrix
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    Chapter 100111 Differential Prediction
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    Chapter 100112 Dimensionality Reduction on Text via Feature Selection
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    Chapter 100113 Directed Graphs
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    Chapter 100115 Distance
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    Chapter 100116 Distance Functions
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    Chapter 100117 Distance Measures
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    Chapter 100118 Distance Metrics
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    Chapter 100119 Distribution-Free Learning
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    Chapter 100120 Document Categorization
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    Chapter 100121 Domain Adaptation
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    Chapter 100504 Absolute Error Loss
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    Chapter 100505 Adaptive System
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    Chapter 100506 Attribute Selection
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    Chapter 100507 A/B Testing
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    Chapter 100508 AQ
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    Chapter 100509 ART
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    Chapter 100514 Data Augmentation
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    Chapter 100515 Data Cleaning
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    Chapter 100516 Data Integration
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    Chapter 100517 Data Scrubbing
Attention for Chapter 6: Adaptive Resonance Theory
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