Brain Tumor Classification Using Machine Learning and Deep Learning Algorithms

Early identification and diagnosis of brain tumors have been a difficult problem. Many approaches proposed using machine learning techniques recent study has explored deep which are the subset learning. In this analysis, Feature extraction such as GLCM, Haralick, GLDM, LBP applied to Brain tumor dataset extract different features from MRI images. The extracted trained classification algorithms SVM, Decision Tree, Random Forest. Performances traditional analyzed accuracy metric stated that with SVM produces better 84.95%. is input three-layer convolutional neural network performance 93.10%. This proves CNN performs well over considered in work.