Used Different visualization techniques to formulate the hypothesis followed by data cleaning and preparation. Use of imbalanced data techniques such as Oversampling and Undersampling methods, and SMOTE were imployed. Finally Naive Bayes algorithm was used to classify the target variable into income groups and XgBoost was used to improve the accuracy of the model.
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sbhmsh28/Project-on-r
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Given data set, our aim is to build the model that predict whether the people earn more than 50k or less than 50k.
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