Text classification experiments on Mongolian language

Text classification is an important task of assigning objects from a universe to two or more classes, especially classification is to classify the topic or the theme of a document. In this research, we have analyzed the result of an experiment on a text classification using Naive Bayesian method approaches for Mongolian language. We have training set of documents, each labeled with one of 10 classes. Since it is the first work in this field for Mongolian language no previous work results were available for comparison.