The goal of this project is to classify ~4000 textual projects from multiple disciplines in the World Bank, for evaluation by the Independant Evaluation Group using Naive Bayes, Kmeans, Random Forest and Neural Network algorithms.
Text classification is a supervised learning task where the algorithm is trained on labeled data to assign predefined categories or labels to documents. The focus is on predicting the predefined classes of documents.