You are hired by one of the leading news channels CNBE who wants to analyze recent elections

You are hired by one of the leading news channels 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. Data Dictionary: 1. vote: Party choice: Conservative or Labour 2. age: in years 3. economic.cond.national: Assessment of current national economic conditions, 1 to 5. 4. economic.cond.household: Assessment of current household economic conditions, 1 to 5. 5. Blair: Assessment of the Labour leader, 1 to 5. 6. Hague: Assessment of the Conservative leader, 1 to 5. 7. Europe: an 11-point scale that measures respondents' attitudes toward European integration. High scores represent ‘Eurosceptic’ sentiment. 8. political.knowledge: Knowledge of parties' positions on European integration, 0 to 3. 9. gender: female or male. 1.1 Read the dataset. Do the descriptive statistics and do the null value condition check. Write inferences on it. 1.2 Perform Univariate and Bivariate Analysis. Do exploratory data analysis. Check for Outliers. Write Inferences. 1.3 Encode the data (having string values) for Modelling? Data Split: Split the data into train and test (70:30). Apply logistic regression on the data to predict the vote. Check the performance of the model. 1.4 Apply clustering on the original data and do cluster profiling. Also, Apply the Silhouette score to evaluate the cluster separation. Divide the data into the number of finalized clusters and apply logistic regression on each cluster separately(treat each cluster as new data). 1.5 Check the Performance Metrics: Check the performance of Predictions on Train and Test sets using Accuracy, Confusion Matrix, classification report, Plot ROC curve, and get ROC_AUC score for Logistic Regression. Comment on the results. 1. 6 Based on these predictions, what are the insights?