I use Python (pandas, numpy, matplotlib, seaborn, and sklearn libraries) to analyze and explore US Census Bureau Data using Data Visualization and Mining techniques to identify salient features useful for predicting an individual's Income level. I use those relevant features to train multiple classification methods (Decision-Tree, SVM, and K-Nearest Neighbor) and predict the income level for unknown individuals. Our client is a local University who wants to use 'income' as the key demographic to decide criteria for marketing its degree programs. Each classifier explored has an accuracy of over 85%.
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I analyze and explore US Census Bureau Data using Data Visualization techniques to identify salient features useful for predicting an individual's income level. We use those relevant features and multiple classification methods (Decision-Tree, SVM, and K-Nearest Neighbor) to predict the income level for unknown individuals. Our client is a local…
jacobtredwell/Data-Visualization-and-Machine-Learning-Classification-Methods-for-Income-Prediction
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I analyze and explore US Census Bureau Data using Data Visualization techniques to identify salient features useful for predicting an individual's income level. We use those relevant features and multiple classification methods (Decision-Tree, SVM, and K-Nearest Neighbor) to predict the income level for unknown individuals. Our client is a local…
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