Prediction of breast cancer using Find-S and Candidate elimination algorithm

Machine learning algorithms are nothing but programs in computes that try to forecast the decisions based on data driven assignment. In diagnosis of cancer the goal is to trained algorithm of machine learning that awards the appearance levels from cancer patient, can precisely predict what type and harshness of cancer they have. Breast cancer is the most delicate and deadly among all of the diseases in medicine. In this paper breast cancer classification is implemented using Find-S and Candidate elimination algorithm. These algorithms are used for the breast cancer detection. Navie Bayes Classifier is used for classification of breast cancer.

[1]  Madhuri Gupta,et al.  A Comparative Study of Breast Cancer Diagnosis Using Supervised Machine Learning Techniques , 2018, 2018 Second International Conference on Computing Methodologies and Communication (ICCMC).

[2]  Sunanda Dixit,et al.  Prediction of Heart Disease Using Random Forest and Rough Set Based Feature Selection , 2019, Coronary and Cardiothoracic Critical Care.

[3]  Karl Rihaczek,et al.  1. WHAT IS DATA MINING? , 2019, Data Mining for the Social Sciences.

[4]  S. Gladston Raj,et al.  A Survey on Breast Cancer Prediction Using Data MiningTechniques , 2018, 2018 Conference on Emerging Devices and Smart Systems (ICEDSS).

[5]  Md. Kamrul Hasan,et al.  Prediction of breast cancer using support vector machine and K-Nearest neighbors , 2017, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC).

[6]  Mohammad Atikur Rahman,et al.  Breast Cancer Prediction Applying Different Classification Algorithm with Comparative Analysis using WEKA , 2018, 2018 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT).

[7]  R. Babu,et al.  Classification of enjoy sport problem using version spaces and the Candidate Elimination algorithm , 2015, 2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015].

[8]  Savita Goel,et al.  A study on prediction of breast cancer recurrence using data mining techniques , 2017, 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence.

[9]  Mohamed Bahaj,et al.  Applying Best Machine Learning Algorithms for Breast Cancer Prediction and Classification , 2018, 2018 International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS).

[10]  Deepika Verma,et al.  Analysis and prediction of breast cancer and diabetes disease datasets using data mining classification techniques , 2017, 2017 International Conference on Intelligent Sustainable Systems (ICISS).

[11]  Sunanda Dixit,et al.  Evaluation of Heart Rate Using Reflectance of an Image , 2016, FICTA.

[12]  Bin Dai,et al.  Using Random Forest Algorithm for Breast Cancer Diagnosis , 2018, 2018 International Symposium on Computer, Consumer and Control (IS3C).

[13]  Nasser H. Sweilam,et al.  Automatic Breast Cancer Detection Using Digital Thermal Images , 2018, 2018 9th Cairo International Biomedical Engineering Conference (CIBEC).

[14]  Palli Suryachandra,et al.  Comparison of machine learning algorithms for breast cancer , 2016, 2016 International Conference on Inventive Computation Technologies (ICICT).

[15]  S. Padmavathi,et al.  Classification of breast cancer dataset by different classification algorithms , 2017, 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS).

[16]  Sunanda Dixit,et al.  Prediction of heart disease using ensemble learning and Particle Swarm Optimization , 2017, 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon).