Project is “Machine Learning Techniques for Prediction and Analysis of Benign and Malignant Tumors Using Binary Classification”. The project uses machine learning algorithms such as Naïve Bayes, SVM-RBF kernel, decision tree, neural networks, and regression tree to predict whether a tumor is benign or malignant. The dataset used in the project contains information on patients’ characteristics such as age, BMI, and menopause status. The project also uses data mining techniques such as feature selection, cross-validation, and model evaluation to improve the accuracy of the prediction models.