Clear View Cancer-AI

Abstract

Abstract: Brest tumor is one of the most dangerous diseases in females. There are a variety of breast cancer; the type of breast cancer depends on which cells turn into cancer. It is so crucial to identify the disease in the early stage so that it can be treated comfortably. Machine learning Machine learning stands out as an exceptionally potent tool to detect cancer in breast. Machine learning facilitates the training of machine and creating some models which can predict the chances of breast cancer . Among the prevalent techniques in machine learning classifier for breast cancer identification are SVM, Naive Bayes, Logistic regression, KNN, Random Forest, AdaBoost, Random Forest, Decision tree, and XGBoost. The motive of this research is to find out the best machine-learning technique which provides the most accuracy for the detection of breast cancer. The precision of machine learning models can differ for dissimilar datasets. This research has been tested across various datasets of large and small sizes and after analyzing the accuracies of these machine learning techniques the conclusion is drawn.