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We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comprehensibility of the rules. However, accuracy and comprehensibility of the rules often conflict with each other. This...
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, current rule based classifiers make use of a small number of rules and a default prediction to build a concise predictive model. This reduces...
The amount of information that police officers come into contact with in the course of their work is astounding. By identifying stages of growth in knowledge management systems and by identifying examples of applications from police investigations, this paper makes an important contribution to...
Recent research has recognised that multicriteria decision making (MCDM) should take account of uncertainty, risk and confidence. This paper takes this research forward by using linguistic variables and triangular fuzzy numbers to model the decision maker’s (DM) risk and confidence attitudes in...
The objective of this study is to present a new algorithm, REX-1, developed for automatic knowledge acquisition in Inductive Learning. It aims at eliminating the pitfalls and disadvantages of the techniques and algorithms currently in use. The proposed algorithm makes use of the direct rule...
One problem in knowledge based systems is the problem of knowledge sharing. Many systems use proprietary frameworks for storing knowledge, and even those systems that use standard knowledge representation formats have the problem that more than one such format exists. Conceptual Graphs and...
Whether a word (or a feature) should be included or excluded during the process of text classification could depend on a number of factors, such as the amount of information it represents, its appearance frequency and its meaning. The application context is another important factor that needs to...
This study proposes a knowledge discovery model that integrates the modification of the fuzzy transaction data-mining algorithm (MFTDA) and the Adaptive-Network-Based Fuzzy Inference Systems (ANFIS) for discovering implicit knowledge in the fuzzy database more efficiently and presenting it more...
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