Logistics enterprise customer classification method based on semi-supervised kernel Fisher discriminant analysis

The invention discloses a logistics enterprise customer classification method based on semi-supervised kernel Fisher discriminant analysis. The logistics enterprise customer classification method is characterized by comprising the following steps: (1) determining customer classification indexes and classification conditions commonly used by logistics enterprises; (2) collecting logistics enterprise customer information according to the customer classification indexes determined in the step (1); (3) standardizing the data sample set in the step (2); (4) constructing a consistency hypothesis matrix for the normalized customer sample data matrix obtained in the step (3), and calculating local inter-class and intra-class Laplace matrixes; (5) calculating a regularization term Laplacian matrixby utilizing the consistency hypothesis matrix obtained in the step (4), integrating the regularization term Laplacian matrix into a Fisher discriminant analysis target function, and obtaining an optimal projection matrix by