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- Huidong Jin, Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
- Inf. Sci.
- 2004

The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capable of projecting high-dimensional data onto a regular, usually 2dimensional grid of neurons with good neighborhood preservation between two spaces. However, due to the dimensional conflict, the neighborhood preservation cannot always lead to perfect topology… (More)

- Wing-Ho Shum, Huidong Jin, Kwong-Sak Leung, Man Leung Wong
- ICDM
- 2002

The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. However, due to the dimensional conflict, the neighborhood preservation cannot always lead to perfect topology preservation. In this paper, we establish an Expanding SOM (ESOM) to detect and preserve better topology correspondence between the two spaces. Our experiment… (More)

- Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
- Fifth IEEE International Conference on Data…
- 2005

Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle discrete values only; it cannot handle continuous, interval and ordinal ones, which must be converted to discrete values and the order information is lost. Thus, BN tends to have… (More)

- Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
- IDEAL
- 2005

A novel Genetic Programming (GP) paradigm called Coevolutionary Rule-Chaining Genetic Programming (CRGP) has been proposed to learn the relationships among attributes represented by a set of classification rules for multi-class problems. It employs backward chaining inference to carry out classification based on the acquired acyclic rule set. Its main… (More)

- Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
- IEEE Congress on Evolutionary Computation
- 2006

Classification rule is a useful model in data mining. Given variable values, rules classify data items into different classes. Different rule learning algorithms are proposed, like Genetic Algorithm (GA) and Genetic Programming (GP). Rules can also be extracted from Bayesian Network (BN) and decision trees. However, all of them have disadvantages and may… (More)

- Wing-Ho Shum, Kwong-Sak Leung, Man-Leung Wong
- 2006 International Multi-Conference on Computing…
- 2006

One objective of data mining is to discover parent-child relationships among a set of variables in the domain. Moreover, showing parents' importance can further help to improve decision makings' quality. Bayesian network (BN) is a useful model for multi-class problems and can illustrate parent-child relationships with no cycle. But it cannot show parents'… (More)

- Wing-Ho Shum
- 2007

- Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
- IEEE International Conference on Computer Systems…
- 2006

Multi-class problem is the class of problems having more than one classes in the data set. Bayesian Network (BN) is a well-known algorithm handling the multi-class problem and is applied to different areas. But BN cannot handle continuous values. In contrast, Genetic Programming (GP) can handle continuous values and produces classification rules. However,… (More)

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