Medical-Expenses-Prediction

• Medical Cost Personal Dataset has been used in this project to predict medical expenses.
• To understand and Predict the medical expenditure of users, I used factors such as age, weight, smoking behaviors, and lifestyle from the dataset to analyze the problem statement.
• Started with performing Univariate, Bivariate analysis on the columns present in the dataset.
• Facetted Charts have been used for Multidimensional visualization and Multivariate analysis.
• Handled with categorical features in the dataset and found useful Insights from Data using EDA.
• In the model creating phase, we used popular regression algorithms such as Linear Regression, Random Forest Regressor has been used and compared the performance between them.
• To boost performance, the Gradient boosting algorithm has been used.
• Built an ensemble model with used algorithms and it's comparative weights.
• Performed cross-validation to increase the model score and reduce the error rate.