Open AccessAn Efficient Data Mining Techniques - Multi-Objective KNN Algorithm to Predict Breast Cancer
Author(s) -
T. Shanmugapriya,
S. Rajalakshmi,
M. Punithavalli
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1188.0882s819
Subject(s) - random forest , decision tree , breast cancer , computer science , data mining , machine learning , data set , health care , set (abstract data type) , artificial intelligence , cancer , medicine , economics , programming language , economic growth
Breast cancer becomes most important foundation of mortality among women. The convenience of medical related dataset and data investigation support to extracting unidentified pattern in medical related or health related dataset. The objective of this research work is is to develop a health care prediction tool predicts the occurrence of the disease at near the beginning level of the criteria by analyzing the collected data set attributes to extract the disease exact level from the medical related information. The projected multi-objective KNN machine learning algorithm (classification) confirms that the highest accuracy (97.16%) is achieved compared to existing decision tree and Random Forest Techniques.