Academic Journal
An Empirical Study of Performance Metrics for Classifier Evaluation in Machine Learning
| Τίτλος: | An Empirical Study of Performance Metrics for Classifier Evaluation in Machine Learning |
|---|---|
| Συνεισφορές: | Bruhns, Stefan, Khoshgoftaar, Taghi M. (Thesis advisor), Florida Atlantic University (Degree grantor) |
| Στοιχεία εκδότη: | Florida Atlantic University |
| Συλλογή: | FAU Digital Collections (Florida Atlantic University Digital Library) |
| Θεματικοί όροι: | Machine learning, Computer algorithms, Pattern recognition systems, Data structures (Computer science), Kernel functions, Pattern perception--Data processing |
| Περιγραφή: | A variety of classifiers for solving classification problems is available from the domain of machine learning. Commonly used classifiers include support vector machines, decision trees and neural networks. These classifiers can be configured by modifying internal parameters. The large number of available classifiers and the different configuration possibilities result in a large number of combinatiorrs of classifier and configuration settings, leaving the practitioner with the problem of evaluating the performance of different classifiers. This problem can be solved by using performance metrics. However, the large number of available metrics causes difficulty in deciding which metrics to use and when comparing classifiers on the basis of multiple metrics. This paper uses the statistical method of factor analysis in order to investigate the relationships between several performance metrics and introduces the concept of relative performance which has the potential to case the process of comparing several classifiers. The relative performance metric is also used to evaluate different support vector machine classifiers and to determine if the default settings in the Weka data mining tool are reasonable. ; College of Engineering and Computer Science ; Thesis (M.S.)--Florida Atlantic University, 2008. ; FAU Electronic Theses and Dissertations Collection |
| Τύπος εγγράφου: | text |
| Περιγραφή αρχείου: | 164 p.; application/pdf; Electronic Thesis or Dissertation |
| Γλώσσα: | English |
| Relation: | FA00012508; http://purl.flvc.org/fau/fd/FA00012508; https://fau.digital.flvc.org/islandora/object/fau%3A39946/datastream/TN/view/An%20Empirical%20Study%20of%20Performance%20Metrics%20for%20Classifier%20Evaluation%20in%20Machine%20Learning.jpg |
| Διαθεσιμότητα: | http://purl.flvc.org/fau/fd/FA00012508 https://fau.digital.flvc.org/islandora/object/fau%3A39946/datastream/TN/view/An%20Empirical%20Study%20of%20Performance%20Metrics%20for%20Classifier%20Evaluation%20in%20Machine%20Learning.jpg |
| Rights: | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. ; http://rightsstatements.org/vocab/InC/1.0/ |
| Αριθμός Καταχώρησης: | edsbas.93DF2453 |
| Βάση Δεδομένων: | BASE |
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