Paper Details

Schizophrenia is a serious mental condition that places a significant clinical burden on patients. In the sphere of health care, choosing the best classification algorithm to categories and forecast disease is more significant. The importance of prediction is determined by the accuracy of the dataset and the machine learning technology used to categories the dataset. Schizophrenia may now be predicted early on because to advances in Machine Learning (ML) Algorithms. In this research paper, we used six classifiers such as Logistic Regression, Naïve Bayes, IBK, AdaBoost, Decision Table, Random Forest. For this classification Weka tool with 10 fold cross validation is used in six classifiers. The Confusion matrix is displayed, along with other relevant data and graphics.