This paper will illustrate the usage of Machine Learning algorithms on US College Scorecard datasets. For this paper, we will use our knowledge, research, and development of a predictive model to compare the results of all the models and predict the public and private net prices. This paper focuses on analyzing US College Scorecard data from data published on government websites. Our goal is to use four machine learning regression models to develop a predictive model to forecast the equitable net cost for every college, encompassing both public institutions and private, whether for-profit or nonprofit.

翻译：本文旨在阐述机器学习算法在美国大学记分卡数据集上的应用。我们将运用所学知识、研究成果，开发预测模型以比较所有模型的结果，并预测公立与私立大学的净价。本文聚焦于分析美国政府网站发布的大学记分卡数据。我们的目标是利用四种机器学习回归模型构建预测模型，以预测每所大学（包括公立、私立营利性及非营利性机构）的公平净成本。