Feature selection and classification of breast cancer diagnosis based on support vector machines

被引：0

作者：

Purnami, Santi Wulan

Rahayu, S. P.

Embong, Abdullah

机构：

来源：

INTERNATIONAL SYMPOSIUM OF INFORMATION TECHNOLOGY 2008, VOLS 1-4, PROCEEDINGS: COGNITIVE INFORMATICS: BRIDGING NATURAL AND ARTIFICIAL KNOWLEDGE | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Support Vector Machines (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. This paper emphasizes how l-norm SVM can be used in feature selection and smooth SVM (SSVM) for classification. As a case studv, a breast cancer diagnosis was implemented. First, feature selection for support vector machines was utilized to determine the important features. Then, SSVM 1,vas used to classify the state of disease (benign or malignant) of breast cancer. As a result, SVM can achieve the state of the art performance on feature selection and classification.

引用

页码：500 / 505

页数：6

共 50 条

[1] Support vector machines combined with feature selection for breast cancer diagnosis
Akay, Mehmet Fatih
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (02) : 3240 - 3247
[2] Prediction model building and feature selection with support vector machines in breast cancer diagnosis
Huang, Cheng-Lung
Liao, Hung-Chang
Chen, Mu-Chen
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (01) : 578 - 587
[3] Feature Selection for Cancer Classification Based on Support Vector Machine
Luo, Wei
Wang, Lipo
Sun, Jingjing
[J]. PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL IV, 2009, : 422 - +
[4] Geographical Classification of Tannat Wines Based on Support Vector Machines and Feature Selection
Costa, Nattane Luiza
Garcia Llobodanin, Laura Andrea
Castro, Inar Alves
Barbosa, Rommel
[J]. BEVERAGES, 2018, 4 (04):
[5] Feature selection and classification of hyperspectral images, with support vector machines
Archibald, Rick
Fann, George
[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2007, 4 (04) : 674 - 677
[6] Feature selection for fast image classification with support vector machines
Fan, ZG
Wang, KA
Lu, BL
[J]. NEURAL INFORMATION PROCESSING, 2004, 3316 : 1026 - 1031
[7] Diagnosis by Support Vector Machines combined with feature selection based on mutual information
Sun, Z.
Xi, G.
Yi, J.
[J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2006, 13E : 736 - 741
[8] Investigating the effect of Correlation based Feature Selection on breast cancer diagnosis using Artificial Neural Network and Support Vector Machines
Alyami, Reem
Alhajjaj, Jinan
Alnajrani, Batool
Elaalami, Ilham
Alqahtani, Abdullah
Aldhafferi, Nahier
Owolabi, Taoreed O.
Olatunji, Sunday O.
[J]. 2017 INTERNATIONAL CONFERENCE ON INFORMATICS, HEALTH & TECHNOLOGY (ICIHT), 2017,
[9] Identification and Analysis of Cancer Diagnosis Using Probabilistic Classification Vector Machines with Feature Selection
Du, Xiuquan
Li, Xinrui
Li, Wen
Yan, Yuanting
Zhang, Yanping
[J]. CURRENT BIOINFORMATICS, 2018, 13 (06) : 625 - 632
[10] Feature selection for support vector machines
Hermes, L
Buhmann, JM
[J]. 15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, PROCEEDINGS: PATTERN RECOGNITION AND NEURAL NETWORKS, 2000, : 712 - 715

← 1 2 3 4 5 →