CS532 Course Project Activity - Climate Data Fitting and Local Warming Justification

Abstract

The project introduce a simplified model to justify whether global warming is truly an issuein the current society. Student will first intensify their knowledge aboutBasis Matrix– itsconstruction and its application to the training process. Student will then construct differentbasis matrix for training, based on their knowledge of global warming, and apply RidgeRegression and LASSO to possibly find the dominant factors of global warming. Studentwill compare the two methods in their ability to select dominant factors of global warming,and then try to justify the authenticity of local warming by scientific soundness of the factorthey choose.Optionally, student will continue to apply their model to other areas around theglobe and try to approach the solution to justify global warming (given sufficient time range).Student will be able to master the construction of Basis Matrix in similar real-worldproblem, and apply the method in compatible with simple machine learning model suchas Ridge Regression and LASSO. Meanwhile, the activity also alarm the pervasive use ofmachine learning in data analysis – researchers shall never overuse machine learning as thesilver bullet to naively derive scientific conclusion.