Searching method and device for distributed model parameter and electronic device
A technology of model parameters and search methods, applied in the field of machine learning, can solve problems such as low efficiency of parameter tuning, and achieve the effect of improving tuning efficiency
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Embodiment 1
[0033] figure 1 It is a flowchart of a search method for distributed model parameters according to an embodiment of the present application.
[0034] refer to figure 1 As shown, the search method provided in this embodiment is used to search the distributed model parameters, so as to find the best parameter combination of the corresponding model, the distributed model parameters are parameters or hyperparameters obtained during model training, The search method specifically includes the following steps:
[0035] S1. Perform verification calculation for each gridded space.
[0036] That is, for each specific grid space, the verification calculation is performed using the pre-acquired verification sample set, so as to obtain the cross-validation mean value of the evaluation index corresponding to each grid space.
[0037] The grid space here refers to the parameter combination or hyperparameter combination obtained by random combination of distributed model parameters obtaine...
Embodiment 2
[0051] image 3 It is a block diagram of a device for searching distributed model parameters according to an embodiment of the present application.
[0052] refer to image 3 As shown, the search device provided in this embodiment is used to search the distributed model parameters, so as to find out the best parameter combination of the corresponding model, the distributed model parameters are parameters or hyperparameters obtained during model training, The search device specifically includes a grid search module 10 , a space narrowing module 20 and a parameter tuning module 30 .
[0053] A grid search module is used to perform validation calculations for each gridded space.
[0054] That is, for each specific grid space, the verification calculation is performed using the pre-acquired verification sample set, so as to obtain the cross-validation mean value of the evaluation index corresponding to each grid space. There are multiple grid search modules here.
[0055] The ...
Embodiment 3
[0068] This embodiment provides an electronic device, which includes at least one processor and a corresponding memory, and the processor and the memory are connected through a corresponding data bus. The memory is used to store computer programs or instructions, and the processor is used to execute computer programs or instructions in order to:
[0069] For each grid space, use the pre-acquired verification sample set to perform verification calculations, and obtain the cross-validation mean value of the evaluation index corresponding to each grid space, and the grid space is the training distributed model. A random combination between the obtained parameters; select the current optimal cross-validation mean value from the obtained multiple cross-validation mean values, and select the most likely local search space according to the current optimal cross-validation mean value; The pre-selected optimal sampling points are subjected to Bayesian optimization calculation in the lo...
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