A genetic based wrapper feature selection approach using nearest neighbour distance matrix
Feature selection for data mining optimization receives quite a high demand especially on high-dimensional feature vectors of a data. Feature selection is a method used to select the best feature (or combination of features) for the data in order to achieve similar or better classification rate.Cur...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/12231/1/05976534.pdf |
| _version_ | 1803626385507352576 |
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| author | Sainin, Mohd Shamrie Alfred, Rayner |
| author_facet | Sainin, Mohd Shamrie Alfred, Rayner |
| author_sort | Sainin, Mohd Shamrie |
| collection | UUM |
| description | Feature selection for data mining optimization
receives quite a high demand especially on high-dimensional feature vectors of a data. Feature selection is a method used to select the best feature (or combination of features) for the data in order to achieve similar or better classification rate.Currently, there are three types of feature selection methods:
filter, wrapper and embedded.This paper describes a genetic based wrapper approach that optimizes feature selection process embedded in a classification technique called a supervised Nearest Neighbour Distance Matrix (NNDM).This method is implemented and tested on several datasets obtained from the UCI Machine Learning Repository and other datasets.The results demonstrate a significant impact on the predictive accuracy for feature selection combined with the supervised NNDM in classifying new instances. Therefore it can be used in other applications that require feature dimension reduction such as image and bioinformatics classifications. |
| first_indexed | 2024-07-04T05:49:20Z |
| format | Conference or Workshop Item |
| id | uum-12231 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T05:49:20Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | uum-122312014-09-30T03:03:04Z https://repo.uum.edu.my/id/eprint/12231/ A genetic based wrapper feature selection approach using nearest neighbour distance matrix Sainin, Mohd Shamrie Alfred, Rayner QA76 Computer software Feature selection for data mining optimization receives quite a high demand especially on high-dimensional feature vectors of a data. Feature selection is a method used to select the best feature (or combination of features) for the data in order to achieve similar or better classification rate.Currently, there are three types of feature selection methods: filter, wrapper and embedded.This paper describes a genetic based wrapper approach that optimizes feature selection process embedded in a classification technique called a supervised Nearest Neighbour Distance Matrix (NNDM).This method is implemented and tested on several datasets obtained from the UCI Machine Learning Repository and other datasets.The results demonstrate a significant impact on the predictive accuracy for feature selection combined with the supervised NNDM in classifying new instances. Therefore it can be used in other applications that require feature dimension reduction such as image and bioinformatics classifications. 2011-06-28 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/12231/1/05976534.pdf Sainin, Mohd Shamrie and Alfred, Rayner (2011) A genetic based wrapper feature selection approach using nearest neighbour distance matrix. In: 3rd Conference on Data Mining and Optimization (DMO), 28-29 June 2011, Putrajaya, Malaysia. http://dx.doi.org/10.1109/DMO.2011.5976534 |
| spellingShingle | QA76 Computer software Sainin, Mohd Shamrie Alfred, Rayner A genetic based wrapper feature selection approach using nearest neighbour distance matrix |
| title | A genetic based wrapper feature selection
approach using nearest neighbour distance matrix |
| title_full | A genetic based wrapper feature selection
approach using nearest neighbour distance matrix |
| title_fullStr | A genetic based wrapper feature selection
approach using nearest neighbour distance matrix |
| title_full_unstemmed | A genetic based wrapper feature selection
approach using nearest neighbour distance matrix |
| title_short | A genetic based wrapper feature selection
approach using nearest neighbour distance matrix |
| title_sort | genetic based wrapper feature selection approach using nearest neighbour distance matrix |
| topic | QA76 Computer software |
| url | https://repo.uum.edu.my/id/eprint/12231/1/05976534.pdf |
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