This article expands from the research of randomness testing of signal generated by superlattice random number generator (SRNG). The thesis tests the generated random signal for this new signal using some common machine learning methods to preprocess one part of random signal and try to train clustering or network model, and then testing other part of random number to judge the quality of randomness. These methods are used on normal distributed random number and SRNG signals, comparison of which shows better performance of SRNG signals.