Zhao, 2006 - Google Patents
Optimal Clustering: Genetic Constrained K-Means and Linear Programming AlgorithmsZhao, 2006
View PDF- Document ID
- 596292667353785458
- Author
- Zhao J
- Publication year
External Links
Snippet
Methods for determining clusters of data under-specified constraints have recently gained popularity. Although general constraints may be used, we focus on clustering methods with the constraint of a minimal cluster size. In this dissertation, we propose two constrained k …
- 230000002068 genetic 0 title abstract description 65
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30587—Details of specialised database models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F17/30 and subgroups
- G06F2216/03—Data mining
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ventura et al. | Pattern mining with evolutionary algorithms | |
Nyathi et al. | Comparison of a genetic algorithm to grammatical evolution for automated design of genetic programming classification algorithms | |
Dehuri et al. | Application of elitist multi-objective genetic algorithm for classification rule generation | |
US7257563B2 (en) | Probabilistic boolean networks | |
Hruschka et al. | A genetic algorithm for cluster analysis | |
Luna et al. | Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules | |
Lampert et al. | Constrained distance based clustering for time-series: a comparative and experimental study | |
US8200589B2 (en) | System and method for network association inference, validation and pruning based on integrated constraints from diverse data | |
Al-Shboul et al. | Initializing k-means using genetic algorithms | |
Garcia-Piquer et al. | Large-scale experimental evaluation of cluster representations for multiobjective evolutionary clustering | |
De Almeida et al. | Fuzzy Kohonen clustering networks for interval data | |
Zarei et al. | Detecting community structure in complex networks using genetic algorithm based on object migrating automata | |
Kalantari et al. | The unreasonable effectiveness of inverse reinforcement learning in advancing cancer research | |
Lensen | Mining feature relationships in data | |
Dehuri et al. | Genetic algorithms for multi-criterion classification and clustering in data mining | |
Kalpana et al. | Cat and Mouse Optimizer with Artificial Intelligence Enabled Biomedical Data Classification. | |
Zhao | Optimal Clustering: Genetic Constrained K-Means and Linear Programming Algorithms | |
Zhao | Optimal Clustering: Genetic Constrained | |
Sotiropoulos et al. | Artificial immune systems | |
Das | The evolution of emergent computation in cellular automata | |
Fu | A comparison of state-of-the-art algorithms for learning bayesian network structure from continuous data | |
Yaveroglu | Graphlet correlations for network comparison and modelling: World trade network example | |
Nyathi | Automated design of genetic programming of classification algorithms. | |
Andreopoulos | Clustering algorithms for categorical data | |
Shand | Evolutionary algorithms in clustering: Challenging problem generation and search space adaptation |