Study on the models of machine learning for better classification

Up to now, with the development of artificial intelligence, artificial energy technology has been widely used in medicine, text recognition, intelligent speech and other fields. As an important branch of artificial intelligence, machine learning plays a pivotal role in accumulating knowledge for artificial intelligence. In order to study better machine learning methods, this paper compares three machine learning models, Gaussian mixture model (GMM), random forest (RF) and hidden Markov model (HMM), analyzes and compares their advantages and disadvantages and better application fields in terms of accuracy and complexity, and combines simple algorithms to explore a model with higher accuracy. Experimental results have validated the model