Feature Selection based on Mutual Information
The application of machine learning models such as support vector machine (SVM) and artificial neural networks (ANN) in predicting reservoir properties has been effective in the recent years when compared with the traditional empirical methods. Despite that the machine learning models suffer a l...
| Main Authors: | , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/13446/ http://ir.unimas.my/id/eprint/13446/1/Feature%20Selection%20based%20on%20Mutual%20Information%20%28abstract%29.pdf |
| _version_ | 1848837411009724416 |
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| author | Muhammad Aliyu, Sulaiman Jane, Labadin |
| author_facet | Muhammad Aliyu, Sulaiman Jane, Labadin |
| author_sort | Muhammad Aliyu, Sulaiman |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The application of machine learning models such as
support vector machine (SVM) and artificial neural networks
(ANN) in predicting reservoir properties has been effective in the
recent years when compared with the traditional empirical
methods. Despite that the machine learning models suffer a lot in
the faces of uncertain data which is common characteristics of
well log dataset. The reason for uncertainty in well log dataset
includes a missing scale, data interpretation and measurement
error problems. Feature Selection aimed at selecting feature
subset that is relevant to the predicting property. In this paper a
feature selection based on mutual information criterion is
proposed, the strong point of this method relies on the choice of
threshold based on statistically sound criterion for the typical
greedy feedforward method of feature selection. Experimental
results indicate that the proposed method is capable of improving
the performance of the machine learning models in terms of
prediction accuracy and reduction in training time. |
| first_indexed | 2025-11-15T06:39:13Z |
| format | Proceeding |
| id | unimas-13446 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:39:13Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-134462017-02-14T05:46:47Z http://ir.unimas.my/id/eprint/13446/ Feature Selection based on Mutual Information Muhammad Aliyu, Sulaiman Jane, Labadin T Technology (General) The application of machine learning models such as support vector machine (SVM) and artificial neural networks (ANN) in predicting reservoir properties has been effective in the recent years when compared with the traditional empirical methods. Despite that the machine learning models suffer a lot in the faces of uncertain data which is common characteristics of well log dataset. The reason for uncertainty in well log dataset includes a missing scale, data interpretation and measurement error problems. Feature Selection aimed at selecting feature subset that is relevant to the predicting property. In this paper a feature selection based on mutual information criterion is proposed, the strong point of this method relies on the choice of threshold based on statistically sound criterion for the typical greedy feedforward method of feature selection. Experimental results indicate that the proposed method is capable of improving the performance of the machine learning models in terms of prediction accuracy and reduction in training time. 2015 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/13446/1/Feature%20Selection%20based%20on%20Mutual%20Information%20%28abstract%29.pdf Muhammad Aliyu, Sulaiman and Jane, Labadin (2015) Feature Selection based on Mutual Information. In: 2015 9th International Conference on IT in Asia (CITA) : Transforming Big Data into Knowledge, 4-5 August 2015, Kuching, Sarawak Malaysia. |
| spellingShingle | T Technology (General) Muhammad Aliyu, Sulaiman Jane, Labadin Feature Selection based on Mutual Information |
| title | Feature Selection based on Mutual Information |
| title_full | Feature Selection based on Mutual Information |
| title_fullStr | Feature Selection based on Mutual Information |
| title_full_unstemmed | Feature Selection based on Mutual Information |
| title_short | Feature Selection based on Mutual Information |
| title_sort | feature selection based on mutual information |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/13446/ http://ir.unimas.my/id/eprint/13446/1/Feature%20Selection%20based%20on%20Mutual%20Information%20%28abstract%29.pdf |