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A longitudinal training method, device, electronic equipment and system of a gbdt model

A training system and model technology, applied in the field of machine learning technology and multi-party secure computing, can solve problems such as the inability to achieve effective training of GBDT models

Active Publication Date: 2022-05-13
HUAKONG TSINGJIAO INFORMATION SCI BEIJING LTD
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  • Claims
  • Application Information

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Problems solved by technology

[0003] At present, in the practical application of the GBDT model, the feature data of various features of multiple samples when training the GBDT model are held by different participants, and these participants do not want to leak multiple samples The feature data of the features held by itself, resulting in the inability to achieve effective training of the GBDT model

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  • A longitudinal training method, device, electronic equipment and system of a gbdt model

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Embodiment Construction

[0057] In order to provide an implementation plan for the longitudinal training of the GBDT model under the condition that each data node participating in the training does not disclose the characteristic data of its own characteristics, the embodiment of the present application provides a method and device for the longitudinal training of the GBDT model , electronic equipment and systems, the preferred embodiments of the present application will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present application, and are not intended to limit the present application. And in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0058] The embodiment of the present application provides a longitudinal training scheme of the GBDT model, such as figure 1 As shown, the...

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Abstract

The present application discloses a longitudinal training method, device, electronic equipment and system of a GBDT model, including: for the current layer of the current decision tree of the initial GBDT model, obtaining the node numbers of the nodes of the current layer for multiple samples respectively; Each node of the current layer, based on the respective node numbers of multiple samples, bins all the samples included in the node according to the number of bins of each feature held by itself, and obtains the binning results; For the various splitting criteria of the node splitting of the current layer, the score gain value of node splitting according to each splitting standard is calculated separately, and the splitting standard with the highest scoring gain value is used as the splitting standard of the current layer; according to the splitting standard, the node splitting is performed, Get the node split result of the current layer and complete the GBDT model training. Using this scheme, the longitudinal training for the GBDT model is realized without each data node revealing its own characteristic data.

Description

technical field [0001] The present application relates to the field of machine learning technology and the field of multi-party secure computing technology, in particular to a longitudinal training method, device, electronic equipment and system of a GBDT model. Background technique [0002] GBDT (Gradient Boosting Decision Tree, Gradient Boosting Decision Tree) is a set of supervised learning algorithms that use decision tree technology for model training. By fitting multiple decision trees, the prediction result of the model is close to the real value used during training. The target value fitted by each decision tree is equal to the difference between the real value of the training set and the predicted value of the previous decision trees. . The GBDT model is usually applied to problems such as classification and regression. [0003] At present, in the practical application of the GBDT model, the feature data of various features of multiple samples when training the GB...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/24323G06F18/214
Inventor 郝天一陈智隆陈琨王国赛
Owner HUAKONG TSINGJIAO INFORMATION SCI BEIJING LTD