Bagging with Randomised Low-Discrepancy Sequences
The 11th Conference on Information Technology and its Applications; Topic: Data Science and AI; pp.43-50.
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2022
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oai:elib.vku.udn.vn:123456789-23112023-09-25T22:32:40Z Bagging with Randomised Low-Discrepancy Sequences Dang, Huu Nghi Bui, Thi Van Anh Bootstrap Aggregation Bagging Low-Discrepancy Sequence Decision Tree The 11th Conference on Information Technology and its Applications; Topic: Data Science and AI; pp.43-50. A Bootstrap Aggregation (or Bagging for short), is a sample of a dataset with replacement. This means that a new dataset is created from a random sample of an existing dataset where a given row may be selected and added more than once to the sample. Consequently, like many randomised algorithms, most Bootstraps use pseudo-random number generators for their random decision making. Similarly, for the implementation of Monte Carlo Methods on computers, pseudo-random generators have been used to simulate the uniform distribution. The performance of the Monte Carlo Methods is known to be heavily dependant on the quality of the pseudo-random generators. In this paper, we investigate the randomised low-discrepancy sequences for Bagging. We experimented with the Bagging of the CART algorithm on some benchmark classification problems using randomised low-discrepancy sequences, and the results were compared with the same bagging using uniform initialisation with a pseudo-random generator. The results show that, Bagging with using randomised low-discrepancy sequences could help the Bootstrap Aggregation improve its performance. 2022-08-17T01:46:33Z 2022-08-17T01:46:33Z 2022-07 Working Paper 978-604-84-6711-1 http://elib.vku.udn.vn/handle/123456789/2311 en application/pdf Da Nang Publishing House |
| institution |
Trường Đại học Công nghệ Thông tin và Truyền thông Việt Hàn - Đại học Đà Nẵng |
| collection |
DSpace |
| language |
English |
| topic |
Bootstrap Aggregation Bagging Low-Discrepancy Sequence Decision Tree |
| spellingShingle |
Bootstrap Aggregation Bagging Low-Discrepancy Sequence Decision Tree Dang, Huu Nghi Bui, Thi Van Anh Bagging with Randomised Low-Discrepancy Sequences |
| description |
The 11th Conference on Information Technology and its Applications; Topic: Data Science and AI; pp.43-50. |
| format |
Working Paper |
| author |
Dang, Huu Nghi Bui, Thi Van Anh |
| author_facet |
Dang, Huu Nghi Bui, Thi Van Anh |
| author_sort |
Dang, Huu Nghi |
| title |
Bagging with Randomised Low-Discrepancy Sequences |
| title_short |
Bagging with Randomised Low-Discrepancy Sequences |
| title_full |
Bagging with Randomised Low-Discrepancy Sequences |
| title_fullStr |
Bagging with Randomised Low-Discrepancy Sequences |
| title_full_unstemmed |
Bagging with Randomised Low-Discrepancy Sequences |
| title_sort |
bagging with randomised low-discrepancy sequences |
| publisher |
Da Nang Publishing House |
| publishDate |
2022 |
| url |
http://elib.vku.udn.vn/handle/123456789/2311 |
| _version_ |
1849201951613386753 |