NDLI: 1-dimensional splines as building blocks for improving accuracy of risk outcomes models

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1-dimensional splines as building blocks for improving accuracy of risk outcomes models

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1-dimensional splines as building blocks for improving accuracy of risk outcomes models

Content Provider	ACM Digital Library
Author	Wang, Morgan C. Vogel, David S.
Abstract	Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maximum linear correlation between the response variable and the predictors, especially when there are non-linear relationships between predictors and the response such as the medical data set used in this study. A spline based transformation method is proposed that is second order smooth, continuous, and minimizes the mean squared error between the response and each predictor. Since the computation time for generating this spline is O(n), the processing time is reasonable with massive data sets. In contrast to cubic smoothing splines, the resulting transformation equations also display a high level of efficiency for scoring. Data used for predicting health outcomes contains an abundance of non-linear relationships between predictors and the outcomes requiring an algorithm for modeling them accurately. Thus, a transformation that fits an adaptive cubic spline to each of a set of variables is proposed. These curves are used as a set of transformation functions on the predictors. A case study of how the transformed variables can be fed into a simple linear regression model to predict risk outcomes is presented. The results show significant improvement over the performance of the original variables in both linear and non-linear models.
Starting Page	841
Ending Page	846
Page Count	6
File Format	PDF
ISBN	1581138881
DOI	10.1145/1014052.1016924
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2004-08-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Adaptive Prediction Risk Data mining Linear model Outcomes Spline Variable transformation
Content Type	Text
Resource Type	Article

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