dc.description.abstract |
The main aspect of this study is to evaluate the different Machine learning classifiers
performance for prediction of breast cancer disease.In this work, we have used six
supervised classification techniques for the classification of breast cancer disease. For
example: SVM, NB, KNN, RF, DT and LR were used for early prediction of breast
cancer. Therefore, we evaluated the breast cancer dataset through sensitivity,
specificity, f 1 measure and total accuracy. The prediction performance of breast cancer
analysis shows that SVM obtained the uppermost performance with utmost
classification accuracy of 97.07%. Whereas, NB and RF has achieved the second
highest accuracy by prediction.Our findings can be used to help reduce the occurrence
of the breast cancer disease through developing a machine learning based predictive
system for early prediction. |
en_US |