Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie?s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to...

We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for SVR the time series decomposed with EMD. The outcomes...

Forecasting the number of warranty claims is vitally important formanufacturers/warranty providers in preparing fiscal plans. In existingliterature, a number of techniques such as log-linear Poisson models, Kalmanfilter, time series models, and artificial neural network models have...

Diabetes has become an important public health issue in the twenty-first century, and dialysis treatment has become a large burden on the National Health Insurance of Taiwan. Diabetic nephropathy(DN) is the leading factor that determines whether patients with diabetes will require dialysis....