Active Learning-Based Pedagogical Rule Extraction

Runtime verification of programs using rule-based active system

Rule Extraction for Transfer Learning

Typically rule extraction is done for the purposes of human interpretation. However, there are other possible applications of rule extraction. One practical application is transfer learning, in which knowledge learned in one task is used to aid in learning a related task. The extracted rules, which explain the learned solution to the first task, can be considered advice on how to approach the s...

Linguistic Rule Extraction by Genetics-Based Machine Learning

This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algorithms. Classification knowledge is extracted in the form of linguistic if-then rules. In this paper, emphasis is placed on the simplicity of the extracted knowledge. The simplicity is measured by two criteria: the numbe...

Learning-based Rule-Extraction from Support Vector Machines

In recent years, support vector machines (SVMs) have shown good performance in a number of application areas, including text classification. However, the success of SVMs comes at a cost – an inability to explain the process by which a learning result was reached and why a decision is being made. Rule-extraction from SVMs is important for the acceptance of this machine learning technology, espec...

Three-objective genetics-based machine learning for linguistic rule extraction

This paper shows how a small number of linguistically interpretable fuzzy rules can be extracted from numerical data for high-dimensional pattern classi®cation problems. One diculty in the handling of high-dimensional problems by fuzzy rule-based systems is the exponential increase in the number of fuzzy rules with the number of input variables. Another diculty is the deterioration in the com...