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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | A Comparative Exploration to Perceive Breast Cancer in Mammograms using Machine Learning Algorithms |
| Authors Name: | T.Leena Prema Kumari , Dr.K.Perumal |
| Unique Id: | IJSDR2005103 |
| Published In: | Volume 5 Issue 5, May-2020 |
| Abstract: | Breast cancer is the most spreading cancer in women and cause death. Early detection or prediction of cancer can be curable and reduce the mortality rate. There are various Machine Learning algorithms to available to find out the purpose and diagnosis Breast Cancer data. In this various Machine Learning algorithm such as Random Forest, Decision Tree, Support Vector Machine, Gradient Boosted Tree and Naïve Bayes were compared for classifying the Breast Cancer dataset. The data set from Kaggle Machine Learning dataset repository was taken. The results of the classification that get from RF, NB, DT, SVM, GBT were compared. The Performance of each technique is evaluated using Performance metrics such as accuracy, sensitivity, recall and precision. The classification result shows that Random forest have the better accuracy as (98.25%) when compare with other algorithms. |
| Keywords: | Random Forest, Decision Tree, Support Vector Machine, Gradient Boosted Tree, Naïve Bayes, Confusion Matrix. |
| Cite Article: | "A Comparative Exploration to Perceive Breast Cancer in Mammograms using Machine Learning Algorithms", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 5, page no.629 - 634, May-2020, Available :http://www.ijsdr.org/papers/IJSDR2005103.pdf |
| Downloads: | 000337071 |
| Publication Details: | Published Paper ID: IJSDR2005103 Registration ID:191847 Published In: Volume 5 Issue 5, May-2020 DOI (Digital Object Identifier): Page No: 629 - 634 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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