Task 1: Classification Model & Model Evaluation Using Titanic train.csv dataset (same as HW1 and 2): [10pt] Use the "survived" as output, and "pclass", "fare", "age", "sex" as input variables. Assuming we are running the analysis on "predicting whether a person will survive". Please do proper cleaning and data transformation (one-hot encoding) on variables if necessary. (we did it in HW2) [50pt] Use the training/testing method on 3 models - logistic regression,decision tree, and SVM. (You can use 80% for training, and 20% for testing) [10pt] Train each model [15pt] Print the accuracy score for each model [5pt] Pick the best model based on accuray score of the testing dataset. [20pt] Use cross validation with 6 folds on 3 models - logistic regression,decision tree, and SVM. [10pt] Train each model using cross validation. [15pt] Get the accuracy score for each model [5pt] Pick the best model