Accuracy Estimation and Comparison of Predictive Algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F00%3A5538" target="_blank" >RIV/62690094:18450/00:5538 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Accuracy Estimation and Comparison of Predictive Algorithms
Original language description
Methods of the knowledge dicovery in databases allow assess information that is hidden in data. Results of data mining, the process of automating information discovery, can be used for predictive decisions. Component parts of predictive data mining are classification algorithms. Building the powerful model is impossible without comparing different algorithms. The use of classification accuracy as the only measure can be missleading in some circumstances. The results of ROC analysis and ROCCH are presented here for detection the dominating model (under different cost and clas distributions). The ROCCH is able to detect models that cannot be dominating under any circumstances. Logistic regression, discriminant analysis, and classification and regressiontress models are compared. Cross validation technique is used. Method ROCCH allowed to specify models that are superior for particular cost and class distribution.
Czech name
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Czech description
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Publication year
2000
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proc. of the 18th Int. Conf. on Math. Methods in Economics
ISBN
80-245-0057-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Czech Society for Operations Research
Place of publication
Praha
Event location
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Event date
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Type of event by nationality
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UT code for WoS article
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