Method, device, apparatus and medium for tuning super-parameters in machine learning model

A machine learning model and hyperparameter technology, applied in the field of machine learning, can solve problems such as consuming a lot of energy and time, relying on personal experience, etc., to achieve the effect of improving development efficiency

Pending Publication Date: 2019-01-18
THE FOURTH PARADIGM BEIJING TECH CO LTD
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Problems solved by technology

[0003] At present, in the training process of the machine learning model, the appropriate hyperparameters are mainly determined through ...

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  • Method, device, apparatus and medium for tuning super-parameters in machine learning model
  • Method, device, apparatus and medium for tuning super-parameters in machine learning model
  • Method, device, apparatus and medium for tuning super-parameters in machine learning model

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[0042] Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0043] figure 1 A flowchart showing a method for tuning hyperparameters in a machine learning model according to an exemplary embodiment of the present invention.

[0044] see figure 1 , in step S110, acquire the template code for training the machine learning model.

[0045] The template code mentioned in the present invention is similar to the code for machine learning (such as deep learning) training, and may include code for performin...

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Abstract

The invention provides a method, a device, an apparatus and a medium for optimizing super parameters in a machine learning model. The method comprises: acquiring a template code for training a machinelearning model, wherein the template code identifies a respective set of values of each of one or more hyperparameters; parsing the template code to identify the respective set of values of one or more super parameters; generating at least partial combinations of values of one or more super parameters based on respective sets of values of the one or more super parameters; acquiring an evaluationresult on a model effect obtained by training a machine learning model according to each of at least partial value combinations; and determining an optimal value of one or more super-parameters of themachine learning model based on the evaluation results. Thus, the consumption of manual parameter adjustment can be reduced, and the development efficiency of machine learning (such as deep learning)can be effectively improved.

Description

technical field [0001] The present invention generally relates to the field of machine learning, and more specifically, relates to a method and device for tuning hyperparameters in a machine learning model, a computing device, and a non-transitory machine-readable storage medium. Background technique [0002] Before training a machine learning model, it is necessary to determine the hyperparameters used when training the machine learning model. Hyperparameters can be regarded as the framework parameters of the machine learning model, which are parameters that describe the machine learning model from a higher level. For example, the hyperparameter may be various parameters describing the learning rate of the machine learning model, the dropout (discarding) rate of the node, the batch size (batch size), and the like. [0003] At present, in the training process of the machine learning model, it is mainly to determine the appropriate hyperparameters through manual parameter ad...

Claims

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Application Information

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IPC IPC(8): G06N20/00
Inventor 裴炜欣赵汉光王珵戴文渊
Owner THE FOURTH PARADIGM BEIJING TECH CO LTD
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