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Model training method and device used in machine learning

A model training and machine learning technology, applied in the field of model training methods and equipment in machine learning, can solve problems such as underfitting and overfitting

Active Publication Date: 2016-07-27
网易有道信息技术(北京)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the more model parameters, the more prone to "overfitting" problems, conversely, the fewer model parameters, the more prone to "underfitting" problems

Method used

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  • Model training method and device used in machine learning
  • Model training method and device used in machine learning
  • Model training method and device used in machine learning

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Embodiment Construction

[0029] The principle and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present invention, rather than to limit the scope of the present invention in any way. 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.

[0030] Those skilled in the art know that the embodiments of the present invention can be implemented as a system, device, device, method or computer program product. Therefore, the present disclosure may be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0031] According to an embodiment of the present invention, a model training method and de...

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PUM

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Abstract

The embodiment of the invention provides a model training method used in machine learning.The method comprises the steps of extracting features from training samples; training a pre-established target model by means of the extracted features, wherein the non-linear part of the target model is expressed as the formula in the description; V belongs to R<k*P>, lambda belongs to R<k*k>, D belongs to R<P*P>, V, lambda and D are the model parameters of the non-linear part of the target model, X belongs to R<P*N> and represents the feature matrix of the training samples, X=(x1, x2,...xi,...xN), xi belongs to R, represents the feature vector of the i training sample and is the column vector of P dimension, and lambda and D are diagonal matrixes.The invention further provides a model training device used in machine learning.

Description

technical field [0001] Embodiments of the present invention relate to the field of machine learning, and more specifically, embodiments of the present invention relate to a model training method and device in machine learning. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein may include concepts that could be explored, but not necessarily concepts that have been previously thought of or explored. Therefore, unless otherwise indicated herein, what is described in this section is not prior art to the description and claims in this application and is not admitted to be prior art by inclusion in this section. [0003] In the process of machine learning, it is necessary to use multiple training samples to train the training model multiple times, and finally obtain a model whose accuracy meets the predetermined requirements, that is, the ideal mode...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F15/18
CPCG06N20/00G06F18/214
Inventor 段亦涛
Owner 网易有道信息技术(北京)有限公司