Problem 1: You are hired by one of the leading news channel CNBE who wants to analyze recent elections. This survey was conducted on 1525 voters with 9 variables. You have to build a model, to predict which party a voter will vote for on the basis of the given information, to create an exit poll that will help in predicting overall win and seats covered by a particular party. Datasetfor Problem: Election Data.xlsx Data Ingestion: 12 marks 1. Read the dataset. Do the descriptive statistics and do null value condition check. Write an inference on it. (5 Marks) 2. Perform Univariate and Bivariate Analysis. Do exploratory data analysis. Check for Outliers. (7' Marks) Data Preparation: 5 marks 1. Encode the data (having string values) for Modelling. Is Scaling necessary here or not? Data Split: Split the data into train and test (T030). (5 Marks) Modelling: 26 marks 1. Apply Logistic Regression and LDA (linear discriminant analysis). (5 marks) 2. Apply KNN Model, Naive Bayes Model and support vector machine (SVM) model. Interpret the results. (7 marks) 3. Model Tuning, Bagging (Random Forest should be applied for Bagging) and Boosting. (?' marks) 4. Performance Metrics: Check the performance of Predictions on Train and Test sets using Accuracy, Confusion Matrix, Plot RUG curve and get ROC_AUC score for each model. Final Model: Compare the models and write inference which model is bestr'optimized. (? marks) Inference: 5 marks 1. Based on these predictions, what are the insights