Analysis of Classification Algorithms for Breast Cancer Prediction

被引:2
|
作者
Rajamohana, S. P. [1 ]
Umamaheswari, K. [1 ]
Karunya, K. [1 ]
Deepika, R. [1 ]
机构
[1] PSG Coll Technol, Dept Informat Technol, Coimbatore 641004, Tamil Nadu, India
来源
DATA MANAGEMENT, ANALYTICS AND INNOVATION, ICDMAI 2019, VOL 1 | 2020年 / 1042卷
关键词
Breast cancer prediction; Classification; Decision tree; Feature selection; K-NN; Random forest; SVM;
D O I
10.1007/978-981-32-9949-8_36
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
According to global statistics, breast cancer is the second of all the fatal diseases that cause death. It will cause an adverse effect when left unnoticed for a long time. However, its early diagnosis provides significant treatment, thus improving the prognosis and the chance of survival. Therefore, accurate classification of the benign tumor is necessary in order to improve the living of the people. Thus, precision in the diagnosis of breast cancer has been a significant topic of research. Even though several new methodologies and techniques are proposed machine learning algorithms and artificial intelligence concepts lead to accurate diagnosis, consequently improving the survival rate of women. The major intent of this research work is to summarize various researches done on predicting breast cancer and classifying them using data mining techniques.
引用
收藏
页码:517 / 528
页数:12
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