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by Zhao Zhang, Li Zhang, Fanzhang Li
Dynamic Fuzzy Machine Learning
Cover
Title Page
Copyright
Contents
Preface
1 Dynamic fuzzy machine learning model
1.1 Problem statement
1.2 DFML model
1.2.1 Basic concept of DFMLs
1.2.2 DFML algorithm
1.2.3 DFML geometric model description
1.2.4 Simulation examples
1.3 Relative algorithm of DFMLS
1.3.1 Parameter learning algorithm for DFMLS
1.3.2 Maximum likelihood estimation algorithm in DFMLS
1.4 Process control model of DFMLS
1.4.1 Process control model of DFMLS
1.4.2 Stability analysis
1.4.3 Design of dynamic fuzzy learning controller
1.4.4 Simulation examples
1.5 Dynamic fuzzy relational learning algorithm
1.5.1 An outline of relational learning
1.5.2 Problem introduction
1.5.3 DFRL algorithm
1.5.4 Algorithm analysis
1.6 Summary
References
2 Dynamic fuzzy autonomic learning subspace algorithm
2.1 Research status of autonomic learning
2.2 Theoretical system of autonomous learning subspace based on DFL
2.2.1 Characteristics of AL
2.2.2 Axiom system of AL subspace
2.3 Algorithm of ALSS based on DFL
2.3.1 Preparation of algorithm
2.3.2 Algorithm of ALSS based on DFL
2.3.3 Case analysis
2.4 Summary
References
3 Dynamic fuzzy decision tree learning
3.1 Research status of decision trees
3.1.1 Overseas research status
3.1.2 Domestic research status
3.2 Decision tree methods for a dynamic fuzzy lattice
3.2.1 ID3 algorithm and examples
3.2.2 Characteristics of dynamic fuzzy analysis of decision trees
3.2.3 Representation methods for dynamic fuzzy problems in decision trees
3.2.4 DFDT classification attribute selection algorithm
3.2.5 Dynamic fuzzy binary decision tree
3.3 DFDT special attribute processing technique
3.3.1 Classification of attributes
3.3.2 Process used for enumerated attributes by DFDT
3.3.3 Process used for numeric attributes by DFDT
3.3.4 Methods to process missing value attributes in DFDT
3.4 Pruning strategy of DFDT
3.4.1 Reasons for pruning
3.4.2 Methods of pruning
3.4.3 DFDT pruning strategy
3.5 Application
3.5.1 Comparison of algorithm execution
3.5.2 Comparison of training accuracy
3.5.3 Comprehensibility comparisons
3.6 Summary
References
4 Concept learning based on dynamic fuzzy sets
4.1 Relationship between dynamic fuzzy sets and concept learning
4.2 Representation model of dynamic fuzzy concepts
4.3 DF concept learning space model
4.3.1 Order model of DF concept learning
4.3.2 DF concept learning calculation model
4.3.3 Dimensionality reduction model of DF instances
4.3.4 Dimensionality reduction model of DF attribute space
4.4 Concept learning model based on DF lattice
4.4.1 Construction of classical concept lattice
4.4.2 Constructing lattice algorithm based on DFS
4.4.3 DF Concept Lattice Reduction
4.4.4 Extraction of DF concept rules
4.4.5 Examples of algorithms and experimental analysis
4.5 Concept learning model based on DFDT
4.5.1 DF concept tree and generating strategy
4.5.2 Generation of DF Concepts
4.5.3 DF concept rule extraction and matching algorithm
4.6 Application examples and analysis
4.6.1 Face recognition experiment based on DF concept lattice
4.6.2 Data classification experiments on UCI datasets
4.7 Summary
References
5 Semi-supervised multi-task learning based on dynamic fuzzy sets
5.1 Introduction
5.1.1 Review of semi-supervised multi-task learning
5.1.2 Problem statement
5.2 Semi-supervised multi-task learning model
5.2.1 Semi-supervised learning
5.2.2 Multi-task learning
5.3 Semi-supervised multi-task learning model based on DFS
5.3.1 Dynamic fuzzy machine learning model
5.3.2 Dynamic fuzzy semi-supervised learning model
5.3.3 DFSSMTL model
5.4 Dynamic fuzzy semi-supervised multi-task matching algorithm
5.4.1 Dynamic fuzzy random probability
5.4.2 Dynamic fuzzy semi-supervised multi-task matching algorithm
5.4.3 Case analysis
5.5 DFSSMTAL algorithm
5.5.1 Mahalanobis distance metric
5.5.2 Dynamic fuzzy K-nearest neighbour algorithm
5.5.3 Dynamic fuzzy semi-supervised adaptive learning algorithm
5.6 Summary
References
6 Dynamic fuzzy hierarchical relationships
6.1 Introduction
6.1.1 Research progress of relationship learning
6.1.2 Questions proposed
6.1.3 Chapter structure
6.2 Inductive logic programming
6.3 Dynamic fuzzy HRL
6.3.1 DFL relation learning algorithm (DFLR)
6.3.2 Sample analysis
6.3.3 Dynamic fuzzy matrix HRL algorithm
6.3.4 Sample analysis
6.4 Dynamic fuzzy tree hierarchical relation learning
6.4.1 Dynamic fuzzy tree
6.4.2 Dynamic fuzzy tree hierarchy relationship learning algorithm
6.4.3 Sample analysis
6.5 Dynamic fuzzy graph hierarchical relationship learning
6.5.1 Basic concept of dynamic fuzzy graph
6.5.2 Dynamic fuzzy graph hierarchical relationship learning algorithm
6.5.3 Sample analysis
6.6 Sample application and analysis
6.6.1 Question description
6.6.2 Sample analysis
6.7 Summary
References
7 Multi-agent learning model based on dynamic fuzzy logic
7.1 Introduction
7.1.1 Strategic classification of the agent learning method
7.1.2 Characteristics of agent learning
7.1.3 Related work
7.2 Agent mental model based on DFL
7.2.1 Model structure
7.2.2 Related axioms
7.2.3 Working mechanism
7.3 Single-agent learning algorithm based on DFL
7.3.1 Learning task
7.3.2 Immediate return single-agent learning algorithm based on DFL
7.3.3 Q-learning function based on DFL
7.3.4 Q-learning algorithm based on DFL
7.4 Multi-agent learning algorithm based on DFL
7.4.1 Multi-agent learning model based on DFL
7.4.2 Cooperative multi-agent learning algorithm based on DFL
7.4.3 Competitive multi-agent learning algorithm based on DFL
7.5 Summary
References
8 Appendix
8.1 Dynamic fuzzy sets
8.1.1 Definition of dynamic fuzzy sets
8.1.2 Operation of dynamic fuzzy sets
8.1.3 Cut set of dynamic fuzzy sets
8.1.4 Dynamic fuzzy sets decomposition theorem
8.2 Dynamic fuzzy relations
8.2.1 The conception dynamic fuzzy relations
8.2.2 Property of dynamic fuzzy relations
8.2.3 Dynamic fuzzy matrix
8.3 Dynamic fuzzy logic
8.3.1 Dynamic fuzzy Boolean variable
8.3.2 DF proposition logic formation
8.4 Dynamic fuzzy lattice and its property
Index
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Prev
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8 Appendix
Index
α-certainty type
1
α-explanatory type
1
Action Choice
1
Agent mental model
1
And/or tree
1
Approximation function
1
Asymptotically stable
1
Attribute-value learning
1
Auto-evaluating
1
Auto-knowledge
1
Auto-monitoring
1
Autonomic Learning
1
Autonomic Learning Space
1
Autonomic Learning Subspace
1
Batch algorithms
1
Bayesian Logic Programs
1
Belie
1
Belief Revision
1
Capacity
1
Classification
1
Cluster Assumption
1
Concept Lattice
1
Concept Learning
1
Connected graph
1
Cooperative multi-agent learning algorithm
1
Cost minimization
1
Critical Value Pruning
1
Curse of dimensionality
1
DF Concept Error Boundary
1
DF concept lattice
1
DF concept lattice critical layer construction algorithm
1
DF Concept Lattice Reduction
1
DF Concept Learning Space Model
1
DF Concept Sample Complexity
1
DF concept tree
1
DF Error Bound Model
1
DF Galois connection
1
DF hypothesis space
1
DF match
1
DF production
1
Direct graph
1
Disconnected graph
1
Discretization
1
Distinguishability
1
Distribution grid
1
Distribution number
1
Division
1
Dundant separation point
1
Dynamic fuzzy association rules
1
Dynamic fuzzy background
1
Dynamic fuzzy binary decision tree
1
Dynamic fuzzy character
1
Dynamic Fuzzy Concepts
1
Dynamic Fuzzy Data
1
Dynamic fuzzy decision tree
1
Dynamic Fuzzy Decision Tree Learning
1
Dynamic Fuzzy Distribution
1
Dynamic fuzzy graph hierarchical relationship learning
1
Dynamic fuzzy graph hierarchical relationship learning
1
Dynamic fuzzy hierarchical relational-learning
1
Dynamic fuzzy hierarchical relationships
1
Dynamic fuzzy information system
1
Dynamic Fuzzy K-Nearest Neighbour Algorithm
1
Dynamic fuzzy lattice
1
Dynamic fuzzy learning controller
1
Dynamic fuzzy logic relation learning algorithm
1
Dynamic Fuzzy Machine Learning
1
Dynamic Fuzzy Machine Learning Model
1
Dynamic Fuzzy Machine Learning Space
1
Dynamic Fuzzy Machine Learning System
1
Dynamic fuzzy matrix
1
Dynamic fuzzy matrix hierarchical relational learning algorithm
1
Dynamic fuzzy mean
1
Dynamic Fuzzy Multi-Task Learning
1
Dynamic fuzzy partitioning grids
1
Dynamic fuzzy random probability
1
Dynamic fuzzy relational learning
1
Dynamic fuzzy relations
1
Dynamic fuzzy rules
1
Dynamic fuzzy semi-supervised adaptive learning algorithm
1
Dynamic fuzzy semi-supervised learning model
1
Dynamic fuzzy semi-supervised multi-task adaptive learning algorithm
1
Dynamic Fuzzy Semi-Supervised Multi-Task Learning
1
Dynamic fuzzy semi-supervised multi-task learning model
1
Dynamic fuzzy semi-supervised multi-task matching algorithm
1
Dynamic Fuzzy Task
1
Dynamic fuzzy tree
1
Dynamic fuzzy tree hierarchical relation learning
1
Dynamic fuzzy variance
1
Error-Based Pruning
1
Estimated error rate
1
Evaluation function
1
Expectation output
1
Extraction of DF concept rules
1
F-direct graph
1
Failure-Adjusted Maximization
1
Flexible rule
1
Generative models
1
Gradual rule
1
Graph
1
Graph Based Relational Learning
1
Graph-based approaches
1
Hierarchical Relational Learning
1
ID3 algorithm
1
Immediate return
1
Improved locally linear embedding
1
Increment algorithms
1
Inductive logic programming
1
Inductive semi-supervised learning
1
Inferential
1
Information entropy
1
Intention Revision
1
Isomorphic
1
Iterative operator
1
Knowledge base
1
Knowledge transfer
1
Laplacian Error Estimation
1
LDA
1
Learnability
1
Learning Space
1
Learning Subspace
1
Least-squares error
1
Linear ordered set
1
Locally linear embedding
1
Logic Hidden Markov Model
1
Logic relation database
1
Low-density division
1
L
-type DF matrix
1
Mahalanobis distance metric
1
Manifold Assumption
1
Markov Logic Network
1
Maximum Likelihood Estimation
1
Metric
1
Minimal Cost Complexity Pruning
1
Minimum Error Pruning
1
Multi-agent learning algorithm based on DFL
1
Multi-Agent Learning Model
1
Multi-task learning
1
Non-direct graph
1
Nonnegativity
1
Order model of DF concept learning
1
Overfit
1
Parameter estimation
1
Partial order relation
1
Pessimistic Error Pruning
1
Post-pruning
1
Pre-pruning
1
Probabilistic Logic Programs
1
Probabilistic Relational Model
1
Probably approximately correct
1
Programming In Statistical Modeling
1
Q-learning algorithm based on DFL
1
Q-learning function based on DFL
1
Reactivity
1
Reduced Error Pruning
1
Regression
1
Regression coefficients
1
Reinforcement learning
1
Relational Markov Model
1
Relational Markov Network
1
Relationship Learning
1
Representation theorem for DF variant space
1
Robust factor
1
Rough Set
1
Sample error rate
1
Self-control
1
Semi-supervised learning
1
Semi-Supervised Multi-Task Learning
1
Semi-supervised multi-task learning model
1
Semi-Supervised Smoothness Assumption
1
Separation point level
1
Simple graph
1
Single-agent learning algorithm based on DFL
1
Soft Decision Tree
1
Stability
1
Statistical Relational Learning
1
Structure Activity Relationship
1
Sub-graph
1
Sub-graph isomorphic
1
Sufficient and necessary condition
1
Symmetry
1
Topological order
1
Transductive learning
1
Transfer learning
1
Triangle inequality
1
True error rate
1
Truncation operation
1
Type L relationship
1
Type-one certainty rule
1
Type-two certainty rule
1
Uncertain dynamic fuzzy autonomous system
1
Unlabelled data
1
VC dimension
1
Weight coefficient
1
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