抄録
In this paper, we propose an improved feature selection method based on genetic algorithms (GA) that achieves both high recognition rates and low numbers of dimensions. This method performs the first search using a GA that uses recognition rate as fitness, and performs the second search with a GA which uses the number of dimensions (reduction) as fitness while avoiding a drop in recognition rate. To speed up the second search,we introduce a special chromosome with maximum reduction quantity that treats all features as unselected as the information source of the GA. We perform experiments using five sets of hand-written Kanji character patterns. Each set consists of patterns in two similar categories. The results show that the proposed method reduces the number of dimensions to 6.2% of the original value wile providing higher recognition rates than the method that uses all features.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 891-899 |
| ページ数 | 9 |
| ジャーナル | Journal of the Institute of Image Electronics Engineers of Japan |
| 巻 | 40 |
| 発行部数 | 5 |
| DOI | |
| 出版物ステータス | Published - 2011 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Electrical and Electronic Engineering
これを引用
“Feature Selection Based on Genetic Algorithms that Achieves High Recognition Rates and Low Numbers of Dimensions and its Application to Character Recognition”. / Suzukl, Akira; Morimoto, Masashi; Yonemura, Shunichi; Shimada, Satoshi.
：: Journal of the Institute of Image Electronics Engineers of Japan, 巻 40, 番号 5, 2011, p. 891-899.研究成果: Article
}
TY - JOUR
T1 - “Feature Selection Based on Genetic Algorithms that Achieves High Recognition Rates and Low Numbers of Dimensions and its Application to Character Recognition”
AU - Suzukl, Akira
AU - Morimoto, Masashi
AU - Yonemura, Shunichi
AU - Shimada, Satoshi
PY - 2011
Y1 - 2011
N2 - In this paper, we propose an improved feature selection method based on genetic algorithms (GA) that achieves both high recognition rates and low numbers of dimensions. This method performs the first search using a GA that uses recognition rate as fitness, and performs the second search with a GA which uses the number of dimensions (reduction) as fitness while avoiding a drop in recognition rate. To speed up the second search,we introduce a special chromosome with maximum reduction quantity that treats all features as unselected as the information source of the GA. We perform experiments using five sets of hand-written Kanji character patterns. Each set consists of patterns in two similar categories. The results show that the proposed method reduces the number of dimensions to 6.2% of the original value wile providing higher recognition rates than the method that uses all features.
AB - In this paper, we propose an improved feature selection method based on genetic algorithms (GA) that achieves both high recognition rates and low numbers of dimensions. This method performs the first search using a GA that uses recognition rate as fitness, and performs the second search with a GA which uses the number of dimensions (reduction) as fitness while avoiding a drop in recognition rate. To speed up the second search,we introduce a special chromosome with maximum reduction quantity that treats all features as unselected as the information source of the GA. We perform experiments using five sets of hand-written Kanji character patterns. Each set consists of patterns in two similar categories. The results show that the proposed method reduces the number of dimensions to 6.2% of the original value wile providing higher recognition rates than the method that uses all features.
KW - character recognition
KW - feature selection
KW - genetic algorithms
KW - number of dimensions
KW - recognition rate
UR - http://www.scopus.com/inward/record.url?scp=85024730841&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85024730841&partnerID=8YFLogxK
U2 - 10.11371/iieej.40.891
DO - 10.11371/iieej.40.891
M3 - Article
AN - SCOPUS:85024730841
VL - 40
SP - 891
EP - 899
JO - Journal of the Institute of Image Electronics Engineers of Japan
JF - Journal of the Institute of Image Electronics Engineers of Japan
SN - 0285-9831
IS - 5
ER -