Detection of Brain Tumor Using Machine Learning Approaches

Abstract

Brain tumor is a very panic issue because many people have died from this problem. Early detection of brain tumors can save many lives. Magnetic resonance imaging (MRI) is more effective than any other technique. In this study, we used an ensemble of machine learning algorithms to identify tumors in the brain at an early stage. We have done our task in several steps. At first, we collect data then analyze and filter the data by using and following tricks and techniques. Next, we use our covetable algorithms. At the end of our task, we found out about our algorithm. The average accuracy of our model is 99.80% and the highest accuracy is 99.20% which contains the XGBoost classifier algorithm. Index Terms—Brain Tumor, Machine Learning, Ensemble, Feature Extraction, XGB, ADB,R