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Benchmark Data Sets (benchmark + data_set)

Distribution by Scientific Domains

Information Science and Computing	50%

Selected Abstracts

Incremental learning of collaborative classifier agents with new class acquisition: An incremental genetic algorithm approach

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 11 2003
Sheng-Uei Guan
A number of soft computing approaches such as neural networks, evolutionary algorithms, and fuzzy logic have been widely used for classifier agents to adaptively evolve solutions on classification problems. However, most work in the literature focuses on the learning ability of the individual classifier agent. This article explores incremental, collaborative learning in a multiagent environment. We use the genetic algorithm (GA) and incremental GA (IGA) as the main techniques to evolve the rule set for classification and apply new class acquisition as a typical example to illustrate the incremental, collaborative learning capability of classifier agents. Benchmark data sets are used to evaluate proposed approaches. The results show that GA and IGA can be used successfully for collaborative learning among classifier agents. © 2003 Wiley Periodicals, Inc. [source]

Dental nomograms for benchmarking based on the study of health in Pomerania data set

JOURNAL OF CLINICAL PERIODONTOLOGY, Issue 12 2004
C. Schwahn
Abstract Aim: Benchmarking is a means of setting goals or targets. On an oral health level, it denotes retaining more teeth and/or improving the quality of life. The goal of this pilot investigation was to assess whether the data generated by a population-based study (SHIP 0) can be used as a benchmark data set to characterize different practice profiles. Material and Methods: The data collected in the population-based study SHIP (n=4310) in eastern Germany were used to generate nomograms of tooth loss, attachment loss, and probing depth. The nomograms included twelve 5-year age strata (20,79 years) presented as quartiles, and additional percentiles of the dental parameters for each age group. Cross-sectional data from a conventional dental office (n=186) and from a periodontology unit (n=130, Greifswald) in the study region as well as longitudinal data set of a another periodontology unit (n=135, Kiel) were utilized in order to verify whether the given practice profile was accurately reflected by the nomogram. Results: In terms of tooth loss, the data from the conventional dental office agree with the median from the nomogram. For attachment loss and probing depth, some age groups yielded slight but not uniform deviations from the median. Cross-sectional data from the periodontology unit Greifswald showed attachment loss higher than the median in younger but not in older age groups. The probing depth was uniformly less than the median and tended toward the 25th percentile with increasing age. The longitudinal data of the Unit of Periodontology in Kiel showed a pronounced trend towards higher percentiles of residual teeth, meaning that the patients retained more teeth. Conclusion: The profile of the Pomeranian dental office does not deviate noticeably from the population-based nomograms. The higher attachment loss of the Unit of Periodontology in Greifswald in younger age strata clearly reflects their selection because of periodontal disease; the combination of higher attachment loss and decreased probing depth may reflect the success of the treatment. The tendency of attachment loss towards the median with increasing age may indicate that the Unit of Periodontology in Greifswald does not fulfill its function as a special care unit in the older subjects. The longitudinal data set of the Unit of Periodontology in Kiel impressively reflects the potential of population-based data sets as a means for benchmarking. Thus, nomograms can help to determine the practice profile, potentially yielding benefits for the dentist, health insurance company, or , as in the case of the special care unit , public health research. [source]

Automatic tuning of L2 -SVM parameters employing the extended Kalman filter

EXPERT SYSTEMS, Issue 2 2009
Tingting Mu
Abstract: We show that tuning of multiple parameters for a 2-norm support vector machine (L2 -SVM) could be viewed as an identification problem of a nonlinear dynamic system. Benefiting from the reachable smooth nonlinearity of an L2 -SVM, we propose to employ the extended Kalman filter to tune the kernel and regularization parameters automatically for the L2 -SVM. The proposed method is validated using three public benchmark data sets and compared with the gradient descent approach as well as the genetic algorithm in measures of classification accuracy and computing time. Experimental results demonstrate the effectiveness of the proposed method in higher classification accuracies, faster training speed and less sensitivity to the initial settings. [source]

Mining temporal rules for software maintenance

JOURNAL OF SOFTWARE MAINTENANCE AND EVOLUTION: RESEARCH AND PRACTICE, Issue 4 2008
David Lo
Abstract Software evolution incurs difficulties in program comprehension and software verification, and hence it increases the cost of software maintenance. In this study, we propose a novel technique to mine from program execution traces a sound and complete set of statistically significant temporal rules of arbitrary lengths. The extracted temporal rules reveal invariants that the program observes, and will consequently guide developers to understand the program behaviors, and facilitate all downstream applications such as verification and debugging. Different from previous studies that were restricted to mining two-event rules (e.g., ,lock,,,unlock,), our algorithm discovers rules of arbitrary lengths. In order to facilitate downstream applications, we represent the mined rules as temporal logic expressions, so that existing model checkers or other formal analysis toolkit can readily consume our mining results. Performance studies on benchmark data sets and a case study on an industrial system have been performed to show the scalability and utility of our approach. We performed case studies on JBoss application server and a buggy concurrent versions system application, and the result clearly demonstrates the usefulness of our technique in recovering underlying program designs and detecting bugs. Copyright © 2008 John Wiley & Sons, Ltd. [source]