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Abstract: Using the theory of machine learning to spectrum cognition and management is a necessary requirement of realizing cognitive radio technology. In order to evaluate the performance of wireless channel spectrum sensing strategy effectively, the statistical mean value is put forward as evaluation criteria for the cognitive user with fixed rate service. Study shows that, for the objective license channel vacancy and occupancy state time with exponentially distribution as well as the same distribution parameter, vacancy state probability follows uniform distribution. Then, the paper analyses how the channel time detection threshold have an influence on throughput. With the increasing of sample size, the estimate of throughput converges in probability to its statistical mean value. Simulation indicates that the spectrum sensing throughput performance of the cognitive user with fixed rate service based on machine learning achieves better performance compared with random spectrum sensing. Ultimately, the channel time detection threshold is achieved when maximizing the statistical mean throughput. [Copyright &y& Elsevier]