2011 EncyclopediaOfMachineLearning Synonyms

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ID Term Page Type Redirect Author(s) mult alp Synonym Cross References GM-RKB Entry
2 Absolute Error Loss 9 S Mean Absolute Error
4 ACO 10 S Ant Colony Optimization
9 Adaptive Control Processes 20 S Bayesian Reinforcement Learning
12 Adaptive Systems 36 S Complexity in Adaptive Systems
14 Agent-Based Computational Models 36 S Artificial Societies
15 Agent-Based Modeling and Simulation 36 S Artificial Societies
17 AIS 36 S Artificial Immune Systems
19 Analogical Reasoning 37 S Instance-Based Learning
20 Analysis of Text 37 S Text Mining
21 Analytical Learning 37 S Deductive Learning ; Explanation-Based Learning
24 AODE 40 S Average One-Dependence Estimators
25 Apprenticeship Learning 40 S Behavioural Cloning
26 Approximate Dynamic Programming 40 S Value Function Approximation
29 AQ 41 S Rule Learning
30 ARL 41 S Average-Reward Reinforcement Learning
31 ART 41 S Adaptive Real-Time Dynamic Programming
32 ARTDP 41 S Adaptive Real-Time Dynamic Programming
39 Associative Bandit Problem 50 S Associative Reinforcement Learning
42 Attribute Selection 54 S Feature Selection
44 AUC 54 S Area Under Curve
46 Average-Cost Neuro-Dynamic Programming 63 S Average-Reward Reinforcement Learning
47 Average-Cost Optimization 63 S Average-Reward Reinforcement Learning
49 Average-Payoff Reinforcement Learning 64 S Average-Reward Reinforcement Learning
52 Backprop 69 S Backpropagation
56 Bandit-Problem with Side Information 73 S Associative Reinforcement Learning
57 Bandit Problem with Side Information 73 S Associative Reinforcement Learning
58 Basic Lemma 73 S Symmetrization Lemma
62 Bayes Adaptive Markov Decision Processes 74 S Bayesian Reinforcement Learning
63 Bayes Net 74 S Bayesian Network
66 Bayesian Model Averaging 81 S Learning Graphical Models
72 Belief State Markov Decision Processes 97 S Partially Observable Markov Decision Processes
78 Bias-Variance Trade-offs 110 S Bias-Variance
81 Binning 111 S Discretization
89 Bounded Differences Inequality 137 S McDiarmid's Inequality
90 BP 137 S Backpropagation
93 C4.5 139 S Decision Tree
97 CART 147 S Decision Tree
98 Cascor 147 S Cascade-Correlation
99 Case 147 S Instance
100 Case-Based Learning 147 S Instance-Based Learning
104 Categorization 159 S Classification ; Concept Learning
105 Category 159 S Class
106 Casual Discovery 159 S learning Graphical Models
108 CBR 166 S Case-Based Reasoning
109 CC 166 S Cascade-Correlation
110 Certainty Equivalence Principle 166 S Internal Model Control
111 Characteristic 166 S Attribute
112 City Block Distance 166 S Manhattan Distance
116 Classification Learning 171 S Concept Learning
117 Classification Tree 171 S Decision Tree
123 Closest Point 179 S Nearest Neighbor
131 Clustering of Nonnumerical Data 183 S Categorical Data Clustering
132 Clustering with Advice 183 S Correlation Clustering
133 Clustering with Constraints 183 S Correlation Clustering
134 Clustering with Qualitative Information 183 S Correlation Clustering
135 Clustering with Side Information 183 S Correlation Clustering
136 CN2 183 S Rule Learning
137 Co-Training 183 S Semi-Supervised Learning
138 Coevolution 183 S Coevolutionary Learning
139 Coevolutionary Computation 184 S Coevolutionary Learning
142 Collection 189 S Class
144 Commercial Email Filtering 193 S Text Mining for Spam Filtering
145 Committee Machines 193 S Ensemble Learning
146 Community Detection 193 S Group Detection
148 Competitive Coevolution 194 S Test-Based Coevolution
150 Complex Adaptive System 194 S Complexity Adaptive Systems
155 Computational Discovery of Quantitative Laws 202 S Equation Discovery
162 Connection Strength 210 S Weight
164 Connectivity 219 S Topology of a Neural Network
169 Content Match 226 S Text Mining for Advertising
171 Content-Based Recommending 226 S Content-Based Filtering
172 Context-Sensitive Learning 226 S Concept Drift
173 Contextual Advertising 226 S Text Mining for Advertising
174 Continual Learning 226 S Life-Long Learning
177 Cooperative Coevolution 226 S Compositional Coevolution
178 Co-Reference Resolution 226 S Entity Resolution
185 Cost-to-Go Function Approximation 235 S Value Function Approximation
187 Covering Algorithm 238 S Rule Learning
197 Data Mining On Text 259 S Text Mining
199 Data Processing 260 S Data Preparation
209 Decision Trees for Regression 267 S Regression Trees
211 Deduplication 267 S Entity Resolution
213 Deep Belief Networks 269 S Deep Belief Nets
216 Dependency Directed Backtracking 274 S Intelligent backtracking
218 Deterministic Decision Rule 274 S Decision Rule
221 Dimensionality Reduction on Text via Feature Selection 279 S Feature Selection in Text Mining
222 Directed Graphs 279 S Digraphs
228 Distance 289 S Similarity Measures
229 Distance Functions 289 S Similarity Measures
230 Distance Measures 289 S Similarity Measures
231 Distance Metrics 289 S Similarity Measures
232 Distribution-Free Learning 289 S PAC Learning
236 Dual Control 298 S Bayesian Reinforcement Learning ; Partially Observable Markov Decision Process
237 Duplicate Detection 298 S Entity Resolution
238 Dynamic Bayesian Network 298 S Learning Graphical Models
239 Dynamic Decision Network 298 S Partially Observable Markov Decision Processes
242 Dynamic Programming for Relational Domains 308 S Symbolic Dynamic Programming
245 EBL 309 S Explanation-Based Learning
246 Echo State Network 309 S Reservoir Computing
247 ECOC 309 S Error Correcting Output Codes
248 Edge Prediction 309 S Link Prediction
250 EFSC 311 S Evolutionary Feature Selection and Construction
251 Elman Network 311 S Simple Recurrent Network
252 EM Algorithm 311 S Expectation Maximization Clustering
253 Embodied Evolutionary Learning 311 S Evolutionary Robotics
259 EP 326 S Expectation Propagation
263 Error 330 S Error Rate
264 Error Correcting Output 331 S ECOC
265 Error Curve 331 S Learning Curves in Machine Learning
268 Estimation of Density Level Sets 331 S Density-Based Clustering
270 Evaluation Data 332 S Test Data ; Test Set
271 Evaluation Set 332 S Test Set
272 Evolution of Agent Behaviors 332 S Evolutionary Robotics
273 Evolution of Robot Control 332 S Evolutionary Robotics
280 Evolutionary Computing 353 S Evolutionary Algorithms
281 Evolutionary Constructive Induction 353 S Evolutionary Feature Selection and Construction
282 Evolutionary Feature Selection 353 S Evolutionary Feature Selection and Construction
284 Evolutionary Feature Synthesis 357 S Evolutionary Feature Selection and Construction
287 Evolutionary Grouping 369 S Evolutionary Clustering
290 Evolving Neural Networks 382 S Neuroevolution
291 Example 382 S Instance
292 Example-Based Learning 382 S Inductive Programming
293 Expectation Maximization Algorithm 382 S Expectation-Maximization Algorithm
297 Experience Curve 387 S Learning Curves in Machine Learning
298 Experience-Based Reasoning 388 S Case-Based Reasoning
300 Explanation-Based Generalization for Planning 388 S Explanation-Based Learning for Planning
306 Feature 397 S Attribute
307 Feature Construction 397 S Data Preparation
309 Feature Extraction 401 S Dimensionality Reduction
310 Feature Reduction 402 S Feature Selection
313 Feature subset 410 S Feature Selection
314 Feedforward Recurrent Network 410 S Simple Recurrent Network
315 Finite Mixture Model 410 S Mixture Model
317 First-Order Predicate Calculus 415 S First-Order Logic
318 First-Order Predicate Logic 415 S First-Order Logic
320 F-Measure 416 S Precision and Recall
321 Foil 415 S Rule Learning
325 Frequent Set 423 S Frequent Itemset
326 Functional Trees 423 S Model trees
333 Generality And Logic 447 S Logic of Generality
336 Generalization Performance 454 S Algorithm Evaluation
337 Generalized Delta Rule 454 S Backpropagation
338 General-to-Specific Search 454 S Learning as Search
342 Genetic Attribute Construction 457 S Evolutionary Feature Selection and Construction
343 Genetic Clustering 457 S Evolutionary Clustering
344 Genetic Feature Selection 457 S Evolutionary Feature Selection and Construction
345 Genetic Grouping 457 S Evolutionary Clustering
346 Genetic Neural Networks 457 S Neuroevolution
348 Genetics-Based Machine Learning 457 S Classifier System
351 Gram Matrix 458 S Kernel Matrix
352 Grammar Learning 458 S Grammatical Interface
354 Grammatical Tagging 459 S POS Tagging
363 Grouping 492 S Categorical Data Clustering
365 Growth Function 492 S Shattering Coefficient
369 Heuristic Rewards 493 S Reward Shaping
372 High-Dimensional Clustering 502 S Document Clustering
374 HMM 506 S Hidden Markov Models
375 Hold-One-Out Error 506 S Leave-One-Out-Error
376 Holdout Data 506 S Holdout Set
383 ID3 515 S Decision Tree
384 Identification 515 S Classification
385 Identity Uncertainty 515 S Entity Resolution
386 Idiot's Bayes 515 S Naïve Bayes
387 Immune Computing 515 S Artificial Immune Systems
389 Immune-Inspired Computing 515 S Artificial Immune Systems
390 Immunocomputing 515 S Artificial Immune Systems
391 Immunological Computation 515 S Artificial Immune Systems
392 Implication 515 S Entailment
393 Improvement Curve 515 S Learning Curves in Machine Learning
397 Induction as Inverted Deduction 522 S Logic of Generality
402 Inductive Inference Rules 528 S Logic of Generality
406 Inductive Program Synthesis 537 S Inductive Programming
410 Inequalities 548 S Generalization Bounds
412 Information Theory 548 S Minimum Description Length Principle ; Minimum Message Length
415 Instance Language 549 S Observation Language
420 Intent Reinforcement Learning 553 S Inverse Reinforcement Learning
424 Inverse Optical Control 554 S Inverse Reinforcement Learning
427 Is More General Than 558 S Logic of Generality
428 Is More Specific Than 558 S Logic of Generality
429 Item 558 S Instance
430 Iterative Classification 558 S Collective Classification
432 Junk Email Filtering 559 S Text Mining for Spam Filtering
438 Kernel Density Estimation 566 S Density Estimation
441 Kernel Shaping 570 S Long Distance Metric Adaptation ; Locally Weighted Regression for Control
442 Kernel-Based Reinforcement Learning 570 S Instance-Based Reinforcement Learning
443 Kernels 570 S Gaussian Process
444 Kind 570 S Class
445 Knowledge Discovery 570 S Text Mining for Semantic Web
446 Kohonen Maps 570 S Self-Organizing Maps
448 L1-Distance 571 S Manhattan Distance
452 Laplace Estimate 571 S Rule Learning
453 Latent Class Model 571 S Mixture Model
457 Learning Bayesian Networks 577 S Learning Graphical Models
458 Learning Bias 577 S Inductive Bias
459 Learning By Demonstration 577 S Behavioral Cloning
460 Learning Classifier Systems 577 S Classifier Systems
461 Learning Control Rules 577 S Behavioral Cloning
463 Learning from Complex Data 580 S Learning from Structured Data
464 Learning from Labeled and Unlabeled Dated 580 S Semi-Supervised Learning
465 Learning from Nonpropositional Data 580 S Learning from Structured Data
466 Learning from Preferences 580 S Preference Learning
469 Learning in Logic 590 S Inductive Logic Programming
470 Learning in Worlds with Objects 590 S Relational Reinforcement Learning
473 Learning with Different Classification Costs 595 S Cost-Sensitive Learning
474 Learning with Hidden Context 595 S Concept Drift
475 Learning Word Senses 595 S Word Sense Disambiguation
476 Least-Squares Reinforcement Learning Methods 595 S Curse of Dimensionality ; Feature Selection ; Radial Basis Functions ; Reinforcement Learning ; Temporal Difference Learning ; Value Function Approximation
478 Lessons-Learned Systems 601 S Case-Base Reasoning
479 Lifelong Learning 601 S Cumulative Learning
480 Life-Long Learning 601 S Continual Learning
484 Linear Regression Tree 606 S Model Trees
486 Link Analysis 606 S Link Mining and Link Discovery
489 Link-Based Classification 613 S Collective Classification
490 Liquid State Machine 613 S Reservoir Computing
492 Local Feature Selection 613 S Projective Clustering
497 Logical Consequence 631 S Entailment
498 Logical Regression Tree 631 S First-Order Regression Tree
500 Logit Model 631 S Logistics Regression
503 LOO Error 632 S Leave-One-Out Error
507 LWPR 632 S Locally Weighted Regression for Control
508 LWR 632 S Locally Weighted Regression for Control
510 m-Estimate 633 S Rule Learning
515 Market Basket Analysis 639 S Basket Analysis
516 Markov Blanket 639 S Graphical Models
517 Markov Chain 639 S Markov Process
520 Markov Model 646 S Markov Process
521 Markov Net 646 S Markov Network
524 Markov Random Field 647 S Markov Network
529 MCMC 652 S Markov Chain Monte Carlo
530 MDL 652 S Minimum Description Length Principle
532 Mean Error 652 S Mean Absolute Error
537 Memory Organization Packets 661 S Dynamic Memory Model
538 Memory-Based 661 S Instance-Based Learning
539 Memory-Based Learning 661 S Case-Based Reasoning
540 Merge-Purge 661 S Entity Resolution
547 Minimum Encoding Inference 668 S Minimum Description Length Principle ; Minimum Message Length
550 Missing Values 680 S Missing Attribute Values
551 Mistake-Bounded Learning 680 S Online Learning
552 Mixture Distribution 680 S Mixture Model
554 Mixture Model 683 S Mixture Model
555 Mode Analysis 683 S Density-Based Clustering
558 Model Space 683 S Hypothesis Space
561 Model-Based Control 689 S Internal Model Control
563 Modularity Detection 693 S Group Detection
564 MOO 693 S Multi- Objective Optimization
565 Morphosyntactic Disambiguation 693 S POS Tagging
567 Most Similar Point 694 S Nearest Neighbor
571 Multi-Armed Bandit 699 S k-Armed Bandit
572 Multi-Armed Bandit Problem 699 S k-Armed Bandit
574 Multi-Criteria Optimization 701 S Multi-Objective Optimization
577 Multiple Classifier Systems 711 S Ensemble Learning
584 NC-Learning 714 S Negative Correlation Learning
585 NCL 714 S Negative Correlation Learning
587 Nearest Neighbor Methods 715 S Instance-Based Learning
590 Network Analysis 716 S LinkMining and Link Discovery
591 Network Clustering 716 S Graph Clustering
592 Networks with Kernel Functions 716 S Radial Basis Function Networks
594 Neural Network Architecture 716 S Topology of a Neural Network
595 Neuro-Dynamic Programming 716 S Value Function Approximation
598 Node 721 S Neuron
603 Nonparametric Bayesian 722 S Gaussian Process
604 Nonparametric Cluster Analysis 722 S Density-Based Clustering
605 Non-Parametric Methods 722 S Instance-Based Learning
607 Nonstationary Kernels 731 S Local Distance Metric Adaptation
608 Nonstationary Kernels Supersmoothing 731 S Locally Weighted Regression for Control
609 Normal Distribution 731 S Gaussian Distribution
613 Object 733 S Instance
614 Object Consolidation 733 S Entity Resolution
615 Object Space 733 S Example Space
618 Ockham's Razor 736 S Occam's Razor
619 Offline Learning 736 S Batch Learning
620 One-Step Reinforcement Learning 736 S Associative Reinforcement Learning
631 Overtraining 744 S Overfitting
633 PAC Identification 745 S PAC Learning
642 Perception 773 S Online Learning
643 Piecewise Constant Models 773 S Regression Trees
644 Piecewise Linear Models 773 S Model Trees
645 Plan Recognition 774 S Inverse Reinforcement Learning
647 Policy Search 776 S Markov Decision Processes ; Policy Gradient Methods
648 POMDPs 776 S Partially Observable Markov Decision Processes
650 Positive Definite 779 S Positive Semidefinite
651 Positive Predictive Value 779 S Precision
653 Posterior 780 S Posterior Probability
660 Predicate Calculus 781 S First-Order Logic
662 Predicate Logic 782 S First-Order Logic
663 Prior Probabilities 782 S Bayesian Nonparametric Models
665 Predication with Expert Advice 782 S Online Learning
666 Predictive Software Model 782 S Predictive Techniques in Software Engineering
672 Prior 795 S Prior Probability
673 Privacy Preserving Data Mining 795 S Privacy-Related Aspects and Techniques
676 Probably Approximately Correct Learning 805 S PAC Learning
678 Program Synthesis From Examples 805 S Inductive Programming
680 Programming by Example 805 S Programming by Demonstration
681 Programming from Traces 806 S Trace-Based Programming
684 Property 812 S Attribute
691 Quadratic Loss 819 S Mean Squared Error
692 Qualitative Attribute 819 S Categorical Attribute
694 Quantitative Attribute 820 S Numeric Attribute
696 Rademacher Average 823 S Rademacher Complexity
698 Radial Basis Function Approximation 823 S Radial Basis Function Networks
700 Radial Basis Function Neural Networks 827 S Radial Basis Function Networks
701 Random Decision Forests 827 S Random Forests
704 Random Subspaces 828 S Random Subspace Method
705 Randomized Decision Rule 828 S Markovian Decision Rule
710 Receiver Operating Characteristic Analysis 829 S ROC Analysis
711 Recognition 829 S Classification
713 Record Linkage 838 S Entity Resolution
714 Recurrent Associative Memory 838 S Hopfield Network
715 Recursive Partitioning 838 S Divide-and-Conquer Learning
716 Reference Reconciliation 838 S Entity Resolution
720 Regularization Networks 849 S Radial Basis Function Networks
722 Reinforcement Learning in Structured Domains 851 S Relational Reinforcement Learning
724 Relational Data Mining 851 S Inductive Logic-Programming
725 Relational Dynamic Programming 851 S Symbolic Dynamic Programming
727 Relational Regression Learning 857 S First-Order Regression Tree
729 Relational Value Iteration 862 S Symbolic Dynamic Programming
730 Relationship Extraction 862 S Link Prediction
732 Representation Language 863 S Hypothesis Language
734 Resolution 863 S First-Order Logic
737 Reward Selection 863 S Reward Shaping
739 RIPPER 865 S Rule Learning
745 RSM 875 S Random Subspace Method
748 Sample Complexity 881 S Generalization Bounds
750 Saturation 881 S Bottom Clause
751 SDP 881 S Symbolic Dynamic Programming
752 Search Bias 881 S Learning as Search
754 Self-Organizing Feature Maps 886 S Self-Organizing Maps
756 Semantic Mapping 888 S Text Visualization
762 Sequence Data 902 S Sequential Data
764 Sequential Inductive Transfer 902 S Cumulative Learning
765 Sequential Prediction 902 S Online Learning
766 Set 902 S Class
770 Simple Bayes 906 S Naïve Bayes
772 SMT 906 S Statistical Machine Translation
774 Solving Semantic Ambiguity 906 S Word Sense Disambiguation
775 SOM 906 S Self-Organizing Maps
776 SORT 906 S Class
777 Spam Detection 906 S Text Mining for Spam Filtering
788 Stacking 912 S Stacked Generalization
789 Starting Clause 912 S Bottom Clause
791 Statistical Learning 912 S Inductive Learning
793 Statistical Natural Language Processing 916 S Maximum Entropy Models for Natural Language Processing
800 Structural Credit Assignment 929 S Credit Assignment
802 Structure 930 S Topology of a Neural Network
803 Structured Data Clustering 930 S Graph Clustering
807 Subspace Clustering 937 S Projective Clustering
809 Supersmoothing 938 S Local Distance Metric Adaptation
815 Symbolic Regression 954 S Equation Discovery
817 Synaptic E. Cacy 954 S Weight
819 Tagging 955 S POS Tagging
820 TAN 955 S True Augmented Naïve Bayes
821 Taxicab Norm Distance 955 S Manhattan Distance
823 TDIDT Strategy 956 S Divide-and-Conquer Learning
824 Temporal Credit Assignment 956 S Credit Assignment
825 Temporal Data 956 S Time Series
828 Test Instances 962 S Test Data
832 Text Clustering 962 S Document Clustering
833 Text Learning 962 S Text Mining
839 Text Spatialization 980 S Text Visualization
842 Threshold Phenomena in Learning 987 S Phase Transitions in Machine Learning
843 Time Sequence 987 S Time Series
845 Topic Mapping 988 S Text Visualization
848 Training Curve 989 S Learning Curves in Machine Learning
850 Training Examples 989 S Training Data
851 Training Instances 990 S Training Data
854 Trait 990 S Attribute
855 Trajectory Data 990 S Semi-Supervised Learning ; Semi-Supervised Text Processing
856 Transfer of Knowledge Across Domains 990 S Inductive Transfer
860 Tree-Based Regression 999 S Regression Trees
862 True Negative Rule 999 S Specificity
864 True Positive Rate 999 S Sensitivity
865 Type 999 S Class
866 Typical Complexity of Learning 999 S Phase Transitions in Machine Learning
869 Unit 1001 S Neuron
871 Unknown Attribute Values 1008 S Missing Attribute Values
872 Unknown Values 1008 S Missing Attribute Values
874 Unsolicited Commercial Email 1008 S Text Mining for Spam Filtering
877 Unsupervised Learner on Document Datasets 1009 S Document Clustering
878 Utility Problem 1009 S Explanation-Based Learning
880 Variable Selection 1021 S Feature Selection
881 Variable Subset Selection 1021 S Feature Selection
882 Variance 1021 S Bias Variance Decomposition
883 Variance Hint 1021 S Variance Bias
885 Vector Optimization 1024 S Multi-Objective Optimization
888 Web Advertising 1027 S Text Mining for Advertising
890 Within-Sample Evaluation 1027 S In-Sample Evaluation