Machine Learning Methods and Applications This section includes some Machine Learning applications and reports using R. Contents 1.Training Linear Regression Model (R) →Report →Code 2.Training a Logistic Regression Model (R) →Report →Code 3.Training Multinomial Regression Model (R) →Report →Code 4.Using Feature Engineering Methods to Improve Model Performance (R) →Report →Code 5.Performance comparison of models trained with Decision Trees and Multivariate (R) →Report →Code 6.Performance comparison of models trained with Decision Trees and Linear Regression methods (R) →Report →Code 7.Performance comparison of Regression Model, Regression Tree, Bagging Tree and Random Forest (R) →Report →Code 8.Performance comparison of Regression Model, Regression Tree, Bagging Tree, Random Forest and Gradient Boosted Model (R) →Report →Code