Abstract:
With advancement of technology in Sri Lanka, use of Sinhala text usage has grown rapidly over the time where
automatic categorization is helpful for efficient content management. As a result, experts tend to use machine learning
application to categorize this large volume of data in an efficient and accurate manner. Most of these learning models
are operating in a black-box where there is no way to understand how the model has decided which category an
instance is assigned. Understanding the reason behind why learning model makes these predictions is very important to
trust such models and to provide reasonable justifications in real world application. Intention of this research is to
present the work carried on related to document classification model prediction interpretation where a set of text
classifiers has been studied with use of SinNG5, freely available Sinhala Document corpus
