A model evaluation method, electronic device, and computer-readable storage medium
A model and decision-making model technology, applied in the field of electronic equipment and computer-readable storage media, and model evaluation methods, can solve problems such as high complexity, high complexity of particle swarm algorithm, and low evaluation efficiency of decision-making models, so as to improve evaluation efficiency Effect
Active Publication Date: 2021-11-19
TENCENT TECH (SHENZHEN) CO LTD
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However, when using particle swarm optimization to achieve multi-factor optimization, it involves the number of factors in the particle swarm, the speed in the particle search process, the maximum speed, the frequency of message synchronization and the number of iterations, etc., so the complexity of the particle swarm optimization Therefore, when the particle swarm optimization algorithm is used to realize the multi-factor optimization in the decision-making model evaluation process, the complexity is high, resulting in low evaluation efficiency of the decision-making model
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[0052] In order to make the purpose, technical solutions and advantages of the application clearer, the application will be further described in detail below in conjunction with the accompanying drawings. All other embodiments obtained under the premise of creative labor belong to the scope of protection of this application.
[0053] In the following description, references to "some embodiments" describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or a different subset of all possible embodiments, and Can be combined with each other without conflict.
[0054] In the following description, the terms "first\second\third\fourth" are only used to distinguish similar objects, and do not represent a specific ordering of objects. Understandably, "first\second\third\fourth" Three\fourth"can be interchanged with specific order or sequential order under permitted circumstances, so that the embodiments of the present applicat...
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The present application provides a model evaluation method, electronic equipment, and a computer-readable storage medium; the method includes: obtaining K factor groups and K first lookup values corresponding to each factor group; performing the following processing through iteration i: obtaining The i-th decision value corresponding to the K i-th search value; based on the comparison result between the i-th decision value and the decision threshold, the K factor groups are divided into the first factor group and the second factor group; the first factor group The i-th lookup value of the target factor in is updated to each factor group in the second factor group; in the first factor group and the updated second factor group, for the i-th target factor of each factor group The second search value is searched in half, and the K i+1th search values corresponding to each factor group are obtained; based on the K first I search values corresponding to each factor group obtained by iteration i, the optimal combination value is determined, and Evaluate a decision model based on the optimal combination of values. Through the present application, the evaluation efficiency of the decision-making model can be improved.
Description
technical field [0001] The present application relates to model evaluation technology in the field of computer application, in particular to a model evaluation method, electronic equipment and computer-readable storage medium. Background technique [0002] In the evaluation process of a decision-making model involving multiple factors, there is often a multi-factor optimization process. Among them, multi-factors refer to multiple factors that affect the decision-making of the decision-making model, and optimization refers to maximizing or minimizing the decision-making value of the decision-making model. process. [0003] Generally speaking, the multi-factor optimization in the evaluation process of the decision-making model can be realized by the particle swarm optimization algorithm. However, when the particle swarm optimization algorithm is used to realize multi-factor optimization, it involves the number of factors in the particle swarm, the speed in the particle search...
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IPC IPC(8): G06F11/36G06N5/00G06N3/00
CPCG06F11/3608G06N5/00G06N3/006
Inventor 赵菁李旭冬袁明凯黄斌罗章龙严明
Owner TENCENT TECH (SHENZHEN) CO LTD