Breast Cancer Detection

DocMusher

Hi RM friends,

For scientists or medical professionals interested in breast cancer detection, here is the link with the project. https://github.com/Ankitadutta2/Data-Mining-for-Breast-Cancer-Detection-using-RapidMiner

The text related with the project can be found here: https://github.com/Ankitadutta2/Data-Mining-for-Breast-Cancer-Detection-using-RapidMiner/blob/master/Team5_MiningReport.pdf

Cheers

Sven

 

#cancer #health #medicine

User141505

HI. interesting. i am looking for some applications in real life data in breast cancer. I took the same dataset and performed a few more tests with the following results.

KNN

accuracy: 92.63% +/- 3.38% (micro average: 92.62%)

Deep Learning

accuracy: 97.37% +/- 2.37% (micro average: 97.36%)

Logistic regression

accuracy: 95.43% +/- 1.48% (micro average: 95.43%)

NaiveBayes

accuracy: 92.97% +/- 2.98% (micro average: 92.97%)

Decision Tree

accuracy: 92.97% +/- 3.70% (micro average: 92.97%)

Random Forest

accuracy: 95.43% +/- 2.37% (micro average: 95.43%)

In my opinion stability is important as well (in this case the more stable model seems to be Logistic regression).
The more accurate and yet stable is deep learning (as highlighted from the ROC analisys). I attach a few screenshots.