Develop a prediction model for the damt variable

Reference no: EM133496864

Assignment: Charitable Organization Classification and Prediction Models Paper & Worksheet

Project Requirements

Question I. Conduct exploratory data analysis on the data set prior to building classification and prediction models. In the report, do not devote a lot of space to discussions of dead-ends, the pursuit of unproductive ideas, technology problems, etc.

Question II. Develop a classification model for the DONR variable using any of the variables as predictors (except ID and DAMT). Fit at least four candidate models (e.g., KNN, Neural Network, regression, random forest; not 4 specifications of the same algorithm) training data and evaluate the fitted models using the validation data. Select a best model that maximizes profit and use your final selected model to classify DONR responses in the score dataset.

Question III. Develop a prediction model for the DAMT variable using any of the variables as predictors (except ID and DONR). Fit at least four candidate models (e.g., linear regression, neural networks, regression trees, etc.) using the training data and evaluate the fitted models using the validation data. Use "average squared error" as the evaluation criteria and use your final selected prediction model to predict DAMT responses in the score dataset.

Question IV. Save your score dataset classifications and predictions into a csv file and submit to Canvas by the project deadline. Also, be sure to submit the project report (word file) by the project deadline.

Question V. Determine the profit (or loss) that you predict your client would have per mailing if they utilized your model to send materials to selected individuals instead of using their mass marketing approach to evaluate your model.

Question VI. You must write up your course project results in a professional report.

Reference no: EM133496864

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