An ensemble framework-stacking and feature selection technique for detection of breast cancer
by Vikas Chaurasia; Saurabh Pal
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 14, No. 3, 2022

Abstract: Breast cancer is the second most common cancer in women worldwide. The machine learning (ML) method is a modern and accurate technique that researchers have recently applied to predict and diagnose breast cancer. In this research article, we developed stack-based ensemble techniques and feature selection methods for the comprehensive performance of the algorithm and comparative analysis of breast cancer datasets with reduced attributes and all attributes. This article uses five-feature selection technique because it affects the overall performance of the model. After applying feature selection method, now we have a dataset with reduced features as well as all features. We implemented logistic regression on a dataset with all features and a dataset with reduced features. Finally, we see that the dataset with reduced features have got improved accuracy.

Online publication date: Tue, 19-Apr-2022

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