Predicting Property Loan Spread Using Segmented Linear Model Final Report
نویسندگان
چکیده
This project attempts to predict the interest spread of a property loan based on the borrower and property related attributes. Each attribute can be regarded as a potential feature. The problem is how to predict the spread accurately based on those features. This report describes our approaches of using linear and segmented linear models as well as other clustering methods. The comparative results and some analysis are also provided. Keywords—Loan Spread; LTV; DSCR; Segmented Linear Regression; MARS; K-means Clustering; PCA
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