Gradient Boosting Machine with Partially Randomized Decision Trees
The gradient boosting machine is a powerful ensemble-based machine learning method for solving regression problems. However, one of the difficulties of its using is a possible discontinuity of the regression function, which arises when regions of training data are not densely covered by training poi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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FRUCT
2021-01-01
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| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://www.fruct.org/publications/fruct28/files/Kon.pdf |
| _version_ | 1818569875288752128 |
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| author | Andrei Konstantinov Lev Utkin Vladimir Muliukha |
| author_facet | Andrei Konstantinov Lev Utkin Vladimir Muliukha |
| author_sort | Andrei Konstantinov |
| collection | DOAJ |
| description | The gradient boosting machine is a powerful ensemble-based machine learning method for solving regression problems. However, one of the difficulties of its using is a possible discontinuity of the regression function, which arises when regions of training data are not densely covered by training points. In order to overcome this difficulty and to reduce the computational complexity of the gradient boosting machine, we propose to apply the partially randomized trees which can be regarded as a special case of the extremely randomized trees applied to the gradient boosting. The gradient boosting machine with the partially randomized trees is illustrated by means of many numerical examples using synthetic and real data. |
| first_indexed | 2024-12-14T06:53:24Z |
| format | Article |
| id | doaj.art-ebab7e19c6824742ac0ff96bbd21ce13 |
| institution | Directory Open Access Journal |
| issn | 2305-7254 2343-0737 |
| language | English |
| last_indexed | 2024-12-14T06:53:24Z |
| publishDate | 2021-01-01 |
| publisher | FRUCT |
| record_format | Article |
| series | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| spelling | doaj.art-ebab7e19c6824742ac0ff96bbd21ce132022-12-21T23:12:49ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372021-01-0128116717310.23919/FRUCT50888.2021.9347631Gradient Boosting Machine with Partially Randomized Decision TreesAndrei Konstantinov0Lev Utkin1Vladimir Muliukha2Peter the Great Saint-Petersburg Polytechnic University, RussiaPeter the Great Saint-Petersburg Polytechnic University, RussiaPeter the Great Saint-Petersburg Polytechnic University, RussiaThe gradient boosting machine is a powerful ensemble-based machine learning method for solving regression problems. However, one of the difficulties of its using is a possible discontinuity of the regression function, which arises when regions of training data are not densely covered by training points. In order to overcome this difficulty and to reduce the computational complexity of the gradient boosting machine, we propose to apply the partially randomized trees which can be regarded as a special case of the extremely randomized trees applied to the gradient boosting. The gradient boosting machine with the partially randomized trees is illustrated by means of many numerical examples using synthetic and real data.https://www.fruct.org/publications/fruct28/files/Kon.pdfmachine learninggradient boosting machinedecision treerandom forest |
| spellingShingle | Andrei Konstantinov Lev Utkin Vladimir Muliukha Gradient Boosting Machine with Partially Randomized Decision Trees Proceedings of the XXth Conference of Open Innovations Association FRUCT machine learning gradient boosting machine decision tree random forest |
| title | Gradient Boosting Machine with Partially Randomized Decision Trees |
| title_full | Gradient Boosting Machine with Partially Randomized Decision Trees |
| title_fullStr | Gradient Boosting Machine with Partially Randomized Decision Trees |
| title_full_unstemmed | Gradient Boosting Machine with Partially Randomized Decision Trees |
| title_short | Gradient Boosting Machine with Partially Randomized Decision Trees |
| title_sort | gradient boosting machine with partially randomized decision trees |
| topic | machine learning gradient boosting machine decision tree random forest |
| url | https://www.fruct.org/publications/fruct28/files/Kon.pdf |
| work_keys_str_mv | AT andreikonstantinov gradientboostingmachinewithpartiallyrandomizeddecisiontrees AT levutkin gradientboostingmachinewithpartiallyrandomizeddecisiontrees AT vladimirmuliukha gradientboostingmachinewithpartiallyrandomizeddecisiontrees |