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Genetic Algorithms and Genetic Linkage
This chapter provides a summary of fundamental materials on genetic algorithms. It presents definitions of genetic algorithm terms and briefly...
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A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set
A correct selection of features (attributes) is vital in data mining. For this aim, the complete set of features is constructed. Here are some...
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Incremental Mining on Association Rules
The discovery of association rules has been known to be useful in selective marketing, decision analysis, and business management. An important...
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Modeling TCP/RED: a Dynamical Approach
Today’s Internet applications, such as World Wide Web, file transfer, Usenet news, and remote login, are delivered via Transmission Control Protocol...
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Dynamics of Congestion Control
One reason for the success of TCP and its widespread usage in the Internet is its ability to control network congestion. A TCP source uses implicit...
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Statistical Properties of Chaos in Communication Networks
The behavior of communication networks, like the Internet is complex in many ways. This complexity may have many origins, including the topology of...
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Componentwise Least Squares Support Vector Machines
This chapter describes componentwise Least Squares Support Vector Machines (LS-SVMs) for the estimation of additive models consisting of a sum of...
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Fuzzy Support Vector Machines with Automatic Membership Setting
Support vector machines like other classification approaches aim to learn the decision surface from the input points for classification problems or...
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Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to...
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Memory Modules and the Innate Structure
As the philosopher Miguel de Umamuno (1864-1936) once said, “We live in memory and memory, and our spiritual life is at bottom simply the effort of...
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The Artificial Mind System (AMS), Modules, and Their Interactions
The previous two chapters have been devoted to establishing the novel artificial neural network concept, namely the kernel memory concept, for the...
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Genetic Linkage Learning Techniques
The importance of learning genetic linkage has been discussed in the previous chapter and recognized in the field of genetic and evolutionary...
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Web Mining – Concepts, Applications and Research Directions
From its very beginning, the potential of extracting valuable knowledge from the Web has been quite evident. Web mining, i.e. the application of data...
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Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets
We propose the use of maximal frequent itemsets (MFIs) to derive association rules from tabular datasets. We first present an efficient method to...
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SYNESTHETIC ANALYSIS OF AUDIO-VISUAL DATA
Interaction between two perceptual modalities, seeing and hearing, their interaction and mutual reinforcement in a complex relationship was a subject...
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CONCLUDING REMARKS
The choice of problems presented in this study is intended to emphasize that in some cases even the classical problems of acoustics can be addressed...
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A Comparative Investigation on Model Selection in Binary Factor Analysis
Binary factor analysis has been widely used in data analysis with various applications. Most studies assume a known hidden factors number k or...
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Extraction of Generalized Rules with Automated Attribute Abstraction
We propose a novel method for mining generalized rules with high support and confidence. Using our method, we can obtain generalized rules in which...
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A Careful Look at the Use of Statistical Methodology in Data Mining
Knowledge discovery in databases (KDD) is an inherently statistical activity, with a considerable literature drawing upon statistical science....
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Improved Knowledge Mining with the Multimethod Approach
Automatic induction from examples has a long tradition and represents an important technique used in data mining. Trough induction a method builds a...