A method for screening samples for building a prediction model and a computer program product thereof are provided. When a set of new sample data is added to a dynamic moving window (DMW), a clustering step is performed with respect to all of the sets of sample data within the window for grouping the sets of sample data with similar properties as one group. If the number of the sets of sample data in the largest group is greater than a predetermined threshold, it means that there are too many sets of sample data with similar properties in the largest group, and the oldest sample data in the largest group can be deleted; if smaller than or equal to a predetermined threshold, it means that the sample data in the largest group are quite unique, and should be kept for building or refreshing the prediction model.
|Translated title of the contribution||預測模型之建模樣本的篩選方法及其電腦程式產品|
|Publication status||Published - 2013 Jun 20|