1. A method for training a duration prediction model, comprising: generating an initial duration prediction model with a plurality of attributes related to duration prediction and at least part of possible attribute combinations of said plurality of attributes, in which each of said plurality of attributes and said attribute combinations is included as an item; calculating importance of each item in said duration prediction model with a computer processor; deleting the item having a lowest importance calculated; re-generating a duration prediction model with remaining items; determining whether said re-generated duration prediction model is an optimal model; and repeating said step of calculating importance and the steps following said step of calculating importance with a newly re-generated duration prediction model, if said duration prediction model is determined as not an optimal model.