ClientPulse

This data mining model is designed to analyze and predict client behavior within an organization, helping businesses better understand and strengthen their relationships with customers. By assigning a predictive score, it evaluates the engagement and loyalty of clients, enabling companies to take proactive measures to improve retention.

About Machine Learning Model

The model utilizes advanced data preprocessing, imblearn oversampling, and aggregate classification techniques to handle imbalanced and skewed datasets effectively. Through these methods, it accurately determines the likelihood of client churn based on various characteristics. The dataset for this analysis was sourced from Kaggle, ensuring diverse and real-world applicability.