Fig. 1

Supervised learning method applying to tumor classification. The flow chart illustrates the steps of building a classification model to differentiate brain neoplasms using supervised learning technique. Here, the problem was identified as a classification problem at the initial stage and then the necessary data was collected as the second step. Data pre-processing was executed as the third step and at the fourth step, the data set was split into training and testing sets. Then a suitable ML algorithm for the collected data was selected as the fifth step of the study flow and then, the selected algorithm was trained with the training data as the sixth step. Finally, the developed algorithm was evaluated with the test data and the hyperparameter of the developed model was tuned to reach the optimum accuracy level of the model