Breast cancer is the most common reason for deaths due to cancer. It is very necessary to detect ... more Breast cancer is the most common reason for deaths due to cancer. It is very necessary to detect cancer at early stages. There are various Machine Learning techniques available for the purpose of diagnosis of breast cancer data. This paper presents a Machine Learning model to perform automated diagnosis for breast cancer. This method employed CNN as a classifier model and Recursive Feature Elimination (RFE) for feature selection. Also, five algorithms SVM, Random Forest, KNN, Logistic Regression, Naïve Bayes classifier have been compared in the paper. The system was experimented on BreaKHis 400X Dataset. The performance of the system is measured on the basis of accuracy and precision. Activation function such as ReLu have been used to predict the outcomes in terms of probabilities. Keywords—Breast Cancer, Dataset, CNN, KNN, Naïve Bayes, Random Forest, SVM, Logistic Regression
Breast cancer is the most common reason for deaths due to cancer. It is very necessary to detect ... more Breast cancer is the most common reason for deaths due to cancer. It is very necessary to detect cancer at early stages. There are various Machine Learning techniques available for the purpose of diagnosis of breast cancer data. This paper presents a Machine Learning model to perform automated diagnosis for breast cancer. This method employed CNN as a classifier model and Recursive Feature Elimination (RFE) for feature selection. Also, five algorithms SVM, Random Forest, KNN, Logistic Regression, Naïve Bayes classifier have been compared in the paper. The system was experimented on BreaKHis 400X Dataset. The performance of the system is measured on the basis of accuracy and precision. Activation function such as ReLu have been used to predict the outcomes in terms of probabilities. Keywords—Breast Cancer, Dataset, CNN, KNN, Naïve Bayes, Random Forest, SVM, Logistic Regression
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Papers by Sweta Bhise