Method and device for updating classifying model

Abstract

The present application discloses a method for updating a classification model, comprising: obtaining incremental data within a predetermined period of time from a server providing the user behavior data as a training sample set; determining the number of newly added decision trees; According to the training sample set, the random forest algorithm is used to generate the newly added number of decision trees; the decision trees included in the classification model and the newly generated decision trees are sorted according to the classification effect, and the sequence position is selected from them. High-level, the predetermined number of decision trees; summarizing the selected decision trees to obtain an updated classification model. The present application also provides a device for updating a classification model. With the method provided in this application, since it is not necessary to perform training based on the full amount of data, but to use the incremental update method on the basis of the original classification model, it can improve the efficiency of model training and achieve rapid response to business.

Description

technical field [0001] The present application relates to a classification model based on a decision tree, in particular to a method for updating the classification model. The present application also relates to a device for updating a classification model. Background technique [0002] With the development of Internet technology, a large number of network applications have emerged, such as social networking, online reading, etc. In order to recommend more targeted information to users or perform necessary monitoring and management, network application providers usually need to The operation behavior in the network application is classified and predicted according to the pre-set goals, such as: whether the user belongs to an active group, whether the user's operation behavior has potential risks, etc. In order to improve prediction efficiency and accuracy, classification models are usually used for classification prediction in most network applications. [0003] The so-cal...

AI Technical Summary

Problems solved by technology

[0009] This application provides a method for updating the classification model to solve the problems of low training efficiency and untimely update of the existing classification model update method

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