Predicting Approval of School Funding

Predicting the Approval of a School Funding Proposal Using Derived Text-Analysis Variables & Random Forest Prediction Models Sridevi Pulugurtha This research presents the investigation of data analysis techniques and approaches used to solve a DonorsChoose.org (Non-Profit Educational Funding Organization) statistical problem from Kaggle. The ultimate goal was to predict the approval of a given school-funding proposal via a machine-learning algorithm only using text-analysis data. This was achieved by only using the 2 essay prompts that were submitted for the funding proposal and generating new data with sentimental and grammatical text analysis. [pdf-embedder url=”https://www.diya-research.org/wp-content/uploads/2021/03/Sridevi-Final-Report.pdf” title=”Sridevi – Final Report”]