The data science team at a retail company wants to predict customer churn using a dataset that has 200 continuous numerical characteristics. The Sales department has offered no insights on which characteristics are important for the churn prediction. The Sales department wants to interpret the model and then determine the direct effect of significant characteristics on the model's output. While training a logistic regression model, the data science team has noticed a significant difference in the accuracy of the training and validation datasets. Which of the following options can the data science team use to enhance the model's performance for addressing the given use case? (Select two)