YuhaoZhang00/Tanzania_waterpoint_prediction_study

Prediction of waterpoint status in Tanzania, a data science study ## Tanzania_waterpoint_prediction_study #### by Yuhao Zhang & Yichen Lu, 2223SPR @ UoN This is a data science study aiming at predicting the waterpoint status in Tanzania. You can find the code and the paper (in IEEE format) in the repository. Abstract: Due to the uncertainty of functionality in Tanzania's waterpoints, numerous regions face the challenge of ensuring a stable water supply. The issue poses a threat to the health and well-being of local people. This study aims to use multiple machine learning models to identify the waterpoint functionality in Tanzania. The dataset is obtained from Tanzania Ministry of Water. Data pre-processing is preformed on the dataset, while 2 sub-research questions regarding the geographical attributes and data time attributes are addressed for further criteria selection. The cleaned data is fed into 6 machine learning models for training and validation. The result shows that the Random Forest model outperforms other models in terms of accuracy, precision, recall, and F1-score.