Support Vector Regression Based Time Series Mining Approach for Non-Invasive ICP Assessment

For the data mining based on time series estimation, the existed studies reveal that the Intra-Cranial Pressure (ICP) time series cannot be well estimated when the linear mapping function is used to delineate the relationship between error and feature. To improve the accuracy for ICP estimation, the non-linear support vector regression (SVR) is used to construct the nonlinear function between feature and error. The experiment results showed that the SVR based mapping function is superior to the linear least square based one.