Model training method and device

A model training and model technology, which is applied in the computer field, can solve the problems of large fluctuations in the quality of the estimated model, unstable quality of the estimated model, etc., and achieve the effect of improving the quality of the model

Active Publication Date: 2015-11-11
TENCENT TECH (SHENZHEN) CO LTD +1
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Problems solved by technology

[0005] In order to solve the problem that the model quality of the estimated model whose cost function is a non-convex function fluctuates greatly, and the m...

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Embodiment Construction

[0023] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0024] Please refer to figure 1 , which shows a method flowchart of a model training method provided by an embodiment of the present invention, and the model training method can be applied to a server. The model training method includes:

[0025] Step 101, constructing a model whose cost function is a non-convex function.

[0026] In step 102, a training sample set is obtained, the training sample set includes various training samples used for training the model, and each training sample includes user features, content features, and operation values ​​corresponding to actual actions taken by the user on the content.

[0027] Step 103, train the model according to the training sample set to obtain n candidate models, where n is a posi...

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Abstract

The invention discloses a model training method and device, and belongs to the technical field of computers. The method comprises the following steps: constructing a cost function as a non-convex function model; obtaining a training sample set, wherein the training sample set comprises each training sample used for training the model, and each training sample comprises user characteristics, content characteristics and an operation value corresponding to practical behaviors adopted by the content; according to the training sample set, training the model to obtain n candidate models, wherein n is a positive integer which is greater than one; and determining the candidate model with the highest quality in the n candidate models as an estimated model obtained in the current training. The model training method and device solves the problem of great fluctuation of the model quality of the estimated model of which the cost function is the non-convex function, and achieves the effect that the model quality of the estimated model which is finally obtained by the training.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a model training method and device. Background technique [0002] Content click rate estimation is used to estimate the probability of a user clicking on a content. The influencing factors of content click-through rate include user characteristics and content characteristics, that is, user preferences, different content placement locations, presentation forms, content materials, etc. will affect the estimated value of content click-through rate. Therefore, according to the content clicked by users and The historical data that has not been clicked by the user is used to train the prediction model, and the content click rate is estimated through the prediction model. [0003] An existing model training method includes: constructing a deep neural network; obtaining historical data, and determining each user feature in the historical data, the content feature corresponding to each...

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Application Information

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IPC IPC(8): G06Q10/04G06N3/08
Inventor 金涬李毅邹永强郭志懋薛伟肖磊
Owner TENCENT TECH (SHENZHEN) CO LTD
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