Method and device for predicting service index

A technology of business indicators and indicators, applied in the field of machine learning, can solve the problems of low prediction accuracy and low modeling efficiency, and achieve the effect of good effect, high accuracy and abundant training data

Pending Publication Date: 2019-07-12
ADVANCED NEW TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0004] However, in the conventional technology, in the face of multiple business entities and multiple business indicators, there are often problems such as low modeling efficiency and low prediction accuracy

Method used

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  • Method and device for predicting service index
  • Method and device for predicting service index
  • Method and device for predicting service index

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Experimental program
Comparison scheme
Effect test

Embodiment approach

[0144] According to one embodiment, the loss determination module 544 is configured to:

[0145] determining a total error based on the prediction error corresponding to each of the plurality of samples;

[0146] determining a regularization term for the network parameter;

[0147] The sum of the total error and the regularization term is determined as the loss function.

[0148] In this way, the recurrent neural network is trained by the training unit 54 as a joint model, and the prediction apparatus 500 realizes the prediction of multi-service entities and multi-service indicators by using the recurrent neural network trained by the training unit 54 .

[0149] According to another embodiment, there is also provided a computer-readable storage medium having a computer program stored thereon, which, when the computer program is executed in a computer, causes the computer to execute the combination figure 2 and Figure 4 the described method.

[0150] According to yet anot...

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Abstract

The embodiment of the invention provides a method and a device for predicting a service index executed by a computer. The method comprises: first, obtaining dataset sequences, wherein the data set sequence comprises m data sets which correspond to m continuous time periods and are arranged according to a time sequence, and the ith data set in the m data sets comprises entity characteristics of a to-be-tested service entity in the ith time period and respective index values of a plurality of to-be-tested service indexes of the to-be-tested service entity; inputting the data set sequence into apre-trained recurrent neural network to obtain an output result. Therefore, according to the output result, the index values of the plurality of to-be-tested service indexes of the to-be-tested service entity in the next time period of the mth time period can be determined.

Description

technical field [0001] One or more embodiments of this specification relate to the field of machine learning, and in particular, to a method and apparatus for predicting business indicators of a business entity by using machine learning. Background technique [0002] With the development of computer technology, machine learning has been applied to various technical fields to analyze and predict various business data. In many application scenarios, it is necessary to predict various business indicators of business entities, so that when the predicted value fluctuates greatly, or the predicted value differs greatly from the actual value, early warning or abnormality is found. [0003] For example, in an e-commerce scenario, it is often necessary to predict various indicator sequences of merchants, such as the prediction of the merchant's daily turnover sequence. Some scenarios will involve the joint prediction of multiple indicator sequences, such as simultaneously predicting...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06N3/04G06N3/08
CPCG06Q30/0202G06N3/084G06N3/045
Inventor 张志强周俊李小龙
Owner ADVANCED NEW TECH CO LTD
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