Brain tumor prediction using naÃ¯ve Bayesâ€™ classifier and decision tree algorithms - Shashank Reddy, Danda; Naga Harshitha, Chinta; Mary Belinda, Carmel (International Journal of Engineering and Technology, 2018)
Now a dayâ€™s many advanced techniques are proposed in diagnosing the tumor in brain like magnetic resonance imaging, computer tomography scan, angiogram, spinal tapÂ and biospy. Based on diagnosis it is easy to predict treatment. All of the types of brain tumor are officially reclassified by the World Health Organization. Brain tumors are of 120 types, almost each tumor is having same symptoms and it is difficult to predict treatment. For this regard we are proposing more accurate and efficient algorithm in predicting the type of brain tumor is NaÃ¯ve Bayesâ€™ classification and decision tree algorithm. The main focus is on solving tumor classification problem using these algorithms. Here the main goal is to show that the prediction through the decision tree algorithm is simple and easy than the NaÃ¯ve Bayesâ€™ algorithm.