Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees
The article presents a brief history of creation of decision trees and defines the purpose of the undertaken works. The process of building a classification tree, according to the CHAID method, is shown paying particular attention to the disadvantages, advantages, and characteristics features of thi...
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| Format: | Article |
| Language: | English |
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Military University of Technology, Warsaw, Poland
2021-06-01
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| Series: | Problemy Mechatroniki |
| Subjects: | |
| Online Access: | http://promechjournal.pl/gicid/01.3001.0014.9332 |
| _version_ | 1798045719204986880 |
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| author | Dariusz AMPUŁA |
| author_facet | Dariusz AMPUŁA |
| author_sort | Dariusz AMPUŁA |
| collection | DOAJ |
| description | The article presents a brief history of creation of decision trees and defines the purpose of the undertaken works. The process of building a classification tree, according to the CHAID method, is shown paying particular attention to the disadvantages, advantages, and characteristics features of this method, as well as to the formal requirements that are necessary to build this model. The tree’s building method for UZRGM (Universal Modernised Fuze of Hand Grenades) fuzes was characterized, specifying the features of the tested hand grenade fuzes and the predictors used that are necessary to create the correct tree model. A classification tree was built basing on the test results, assuming the accepted post-diagnostic decision as a qualitative dependent variable. A schema of the designed tree for the first diagnostic tests, its full structure and the size of individual classes of the node are shown. The matrix of incorrect classifications was determined, which determines the accuracy of incorrect predictions, i.e., correctness of the performed classification. A sheet with risk assessment and standard error for the learning sample and the v-fold cross-check were presented. On the selected examples, the quality of the resulting predictive model was assessed by means of a graph of the cumulative value of the lift coefficient and the "ROC" curve
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| first_indexed | 2024-04-11T23:26:51Z |
| format | Article |
| id | doaj.art-b578a45260504da5a68c01dfe0061001 |
| institution | Directory Open Access Journal |
| issn | 2081-5891 |
| language | English |
| last_indexed | 2024-04-11T23:26:51Z |
| publishDate | 2021-06-01 |
| publisher | Military University of Technology, Warsaw, Poland |
| record_format | Article |
| series | Problemy Mechatroniki |
| spelling | doaj.art-b578a45260504da5a68c01dfe00610012022-12-22T03:57:18ZengMilitary University of Technology, Warsaw, PolandProblemy Mechatroniki2081-58912021-06-01122395410.5604/01.3001.0014.933201.3001.0014.9332Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision TreesDariusz AMPUŁA0Military Institute of Armament Technology, Zielonka, PolandThe article presents a brief history of creation of decision trees and defines the purpose of the undertaken works. The process of building a classification tree, according to the CHAID method, is shown paying particular attention to the disadvantages, advantages, and characteristics features of this method, as well as to the formal requirements that are necessary to build this model. The tree’s building method for UZRGM (Universal Modernised Fuze of Hand Grenades) fuzes was characterized, specifying the features of the tested hand grenade fuzes and the predictors used that are necessary to create the correct tree model. A classification tree was built basing on the test results, assuming the accepted post-diagnostic decision as a qualitative dependent variable. A schema of the designed tree for the first diagnostic tests, its full structure and the size of individual classes of the node are shown. The matrix of incorrect classifications was determined, which determines the accuracy of incorrect predictions, i.e., correctness of the performed classification. A sheet with risk assessment and standard error for the learning sample and the v-fold cross-check were presented. On the selected examples, the quality of the resulting predictive model was assessed by means of a graph of the cumulative value of the lift coefficient and the "ROC" curve http://promechjournal.pl/gicid/01.3001.0014.9332mechanical engineeringdecision treesbranchleafnodefeature |
| spellingShingle | Dariusz AMPUŁA Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees Problemy Mechatroniki mechanical engineering decision trees branch leaf node feature |
| title | Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees |
| title_full | Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees |
| title_fullStr | Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees |
| title_full_unstemmed | Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees |
| title_short | Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees |
| title_sort | prediction of post diagnostic decisions for tested hand grenades fuzes using decision trees |
| topic | mechanical engineering decision trees branch leaf node feature |
| url | http://promechjournal.pl/gicid/01.3001.0014.9332 |
| work_keys_str_mv | AT dariuszampuła predictionofpostdiagnosticdecisionsfortestedhandgrenadesfuzesusingdecisiontrees |