Using pulse shape discrimination (PSD) to distinguish between neutrons and gamma rays is an important task in the process of nuclear detection.. Based on the Labview platform, this paper realizes the simulation and signal preprocessing process of n/γ pulse signal. The traditional discrimination method, charge comparison method, pulse gradient analysis (PGA) method, and rise time method are used to perform the n/γ pulse signal screening, screening out the neutron and γ-ray mixed pulse signals with the same results of the above three screening methods as the training set of the KNN classification algorithm. The KNN classification model is constructed by training samples, so that the classification of neutron and gamma-ray pulse signals can be realized through this model. The results show that the accuracy of neutron and gamma-ray pulse waveform discrimination based on the KNN classification algorithm is as high as 99.58%. Compared with the charge comparison method, the rise time method and the PGA method, the discrimination error rate is significantly reduced. And the KNN classification algorithm is simple in principle and easy to implement, so it can be applied to the discrimination of n-γ pulses in the actual mixed field.