Evaluation method based on variable-weight clustering method of gray whitening function

Abstract

The invention discloses an evaluation method based on a variable-weight clustering method of a gray whitening function. The evaluation method comprises the following steps of establishing n clustering units i which represent the number of evaluated objects, wherein n=1, 2, 3, 4, ..., n, and i belongs to I; m clustering indexes j which represents evaluation indexes, wherein j=1, 2, 3, 4, ..., m, and j belongs to J; and s gray evaluations k, wherein k=1, 2, 3, 4, ..., s, and k belongs to K; performing dimensionless standardization processing on original data which are evaluated by the clustering units i;, obtaining a sample matrix of target object according to the sample values of the clustering units i about the clustering indexes j, wherein the elements in the matrix are clustering whitening values of an evaluating object; constructing a plurality of gray whitening weighting functions fjk about the clustering indexes j, wherein each gray whitening weighting function represents an evaluation grade; and determining each clustering coefficient for evaluating the gray, and obtaining the gray of the evaluating object, thereby finishing evaluation.

Description

technical field [0001] The invention relates to an evaluation method and system for evaluating the quality of professional degree postgraduate enrollment, in particular to an evaluation method and system based on gray whitening function variable weight clustering method. Calculation involving patent classification number G06; calculation; counting [0002] G06Q Data processing systems or methods specially adapted for administrative, commercial, financial, management, supervisory or forecasting purposes; processing systems or methods exclusively suitable for administrative, commercial, financial, managerial, supervisory or forecasting purposes not covered by other categories G06Q10 / 00 Administration; Management G06Q10 / 06 Resource, workflow, people or project management, such as organizing, planning, scheduling or allocating time, people or machine resources; enterprise planning; organizational models. Background technique [0003] At present, full-time professional degree p...

AI Technical Summary

Problems solved by technology

It treats all clustering indicators equally and cannot reflect the differences in the role of different indicators in the clustering process.

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