Building an Honest Tree for Mass Spectra Classification Based on Prior Logarithm Normal Distribution

Abstract

Structure elucidation is one of big tasks for analytical researcher and it often needs an efficient classifier. The decision tree is especially attractive for easy understanding and intuitive represen- tation. However, small change in the data set due to the experiment error can often result in a very different series of split. In this pa- per, a prior logarithm normal distribution is adopted to weight the original mass spectra. It helps to building an honest tree for later structure elucidation.