2011 EncyclopediaOfMachineLearning Synonyms

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