The invention provides a
quantum clustering method based on a nearest neighbor KNN and an improved
wave function, and the method comprises the steps: obtaining
original data of a group of to-be-classified sample points, carrying out the normalization of the
original data, determining the input parameters of a
quantum clustering model based on the nearest neighbor KNN, calculating the
wave function parameters of all sample points, and carrying out the calculation of the
wave function parameters of all sample points; the wave function parameters comprise the steps of calculating scale parameters and shape parameters of distribution obeyed by wave functions, calculating
potential energy surfaces of
quantum clustering, and determining the classification number and classification boundaries according to the calculated
potential energy surfaces. The method provided by the invention inherits all advantages of a
quantum clustering method, is more suitable for classifying data obeying Weibull distribution, provides a new choice for
data classification, does not need to manually give any input parameter and does not need to give a classification
label of sample data at the same time, and can be applied to the field of
data classification. The input parameters of the
quantum clustering model can be calculated, the practicability is high, and the accuracy is high.