Authors :
Sawan Verma; Saloni Chaudhary; Sunil Kumar; Pranav Singh Rana
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3A62TIv
DOI :
https://doi.org/10.5281/zenodo.6670565
Abstract :
The breast cancer is very common and a
dominant cancer in women over the world. It is
increasing in countries which are developing and where
most of the cases are prognosed in the late stages. Some
of the strategies which were already suggested or
proposed and shows a comparability between the ML
algo by using various approach such as the ensemble
approach , using blood analysis or Data mining algo
,etc.In this research paper there is a comparability of
the two machine leaning algo RF(Random Forest) and
Decision Tree. The data set was divided into the two
stages that is training stage and the testing stage. The
algo will be used in this application which gives the best
results and then the approach of the model will be
classifies that the cancer just as malignant or benign.
Keywords :
Machine Learning, Breast Cancer, Identification, Classification, Prediction, Random Forest, Decision Tree, Malignant, Benign
The breast cancer is very common and a
dominant cancer in women over the world. It is
increasing in countries which are developing and where
most of the cases are prognosed in the late stages. Some
of the strategies which were already suggested or
proposed and shows a comparability between the ML
algo by using various approach such as the ensemble
approach , using blood analysis or Data mining algo
,etc.In this research paper there is a comparability of
the two machine leaning algo RF(Random Forest) and
Decision Tree. The data set was divided into the two
stages that is training stage and the testing stage. The
algo will be used in this application which gives the best
results and then the approach of the model will be
classifies that the cancer just as malignant or benign.
Keywords :
Machine Learning, Breast Cancer, Identification, Classification, Prediction, Random Forest, Decision Tree, Malignant, Benign
