Comparative study of Relevance Vector Machine with various machine learning techniques used for detecting breast cancer

被引:0
|
作者
Gayathri, B. M. [1 ]
Sumathi, C. P. [2 ]
机构
[1] SDNB Vaishnav Coll women, Madras, Tamil Nadu, India
[2] SDNB Vaishnav Coll women, Dept Comp Sci, Madras, Tamil Nadu, India
关键词
Breast Cancer; Relevance Vector Machine; Machine Learning; Naive Bayes; Analysis of Variance(ANOVA); Linear Discriminant Analysis(LDA); Extreme Learning Machine;
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
Now-a-days breast cancer has become one of the leading cause of cancer death among women. This cancer is caused mostly due to the lifestyle changes, avoiding breast feeding etc. Detecting breast cancer takes long time due to manual diagnosis. Even though there are many diagnostic systems are available still, it takes more time for proper classification. For detecting breast cancer, mostly machine learning techniques are used. This work deals with the comparative study of Relevance vector machine(RVM) which provides Low computational cost while comparing with other machine learning techniques which are used for breast cancer detection. The aim of this work is to compare and explain how RVM is better than other machine learning algorithms for diagnosing breast cancer even the variables are reduced.
引用
收藏
页码:543 / 547
页数:5
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