Software Development and Testing for Machine Learning Studies With an Example of Probabilistic Inference with Monte Carlo Based Methods

Abstract

It is not easy to test software used in studies of machine learning with statistical frameworks. In particular, software for randomized algorithms such as Monte Carlo methods compromises testing process. Combined with underestimation of the importance of software testing in academic fields, many software programs without appropriate validation are being used and causing problems. In this article, we discuss the importance of writing test codes for software used in research, and present a practical way for testing, focusing on programs using Monte Carlo methods. keywords: Monte Carlo methods, machine learning, program development, validation, statistical inference. © 2012, The Japanese Society for Artificial Intelligence. All rights reserved.