Service prediction method and device

A forecasting method and business technology, applied in the field of machine learning, can solve problems such as labor cost waste, business forecast model parameter estimation deviation, and inability to judge various business indicators, so as to reduce cost waste and reduce parameter estimation deviation.

Active Publication Date: 2021-01-08
SHANGHAI ICEKREDIT INC
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The business forecasting model trained in this way cannot obtain the future behavior of those rejected business objects in the subsequent business forecasting, nor can it judge the various business indicators of these business objects, which leads to the existence of parameters in the final business forecasting model. Estimated deviation, resulting in subsequent waste of labor costs

Method used

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  • Service prediction method and device
  • Service prediction method and device

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Embodiment Construction

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the appended The figures are only for the purpose of illustration and description, and are not used to limit the protection scope of the present application. Additionally, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented in accordance with some of the embodiments of this application. It should be understood that the operations of the flowcharts may be performed out of order, and steps that have no logical context may be performed in reverse order or concurrently. In addition, those skilled in the art may add one or more other oper...

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Abstract

The embodiment of the invention provides a service prediction method and device, which considers the data characteristics of part of service samples that are rejected in service verification while considering the service samples passing the service verification, truly restores the service scene, reduces the cost waste of rejected samples, particularly, reasonably balances the requirements of the modeling sample and the rejection sample under the condition that the sample size of samples passing the service verification is insufficient, , so that when the service prediction model obtained by training predicts the received service information to be predicted, the future behavior of the rejected service object can be predicted, and the parameter estimation deviation is reduced.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular, to a service prediction method and device. Background technique [0002] Usually, the business prediction model based on machine learning can evaluate the business indicators of the classification labels to which the business belongs. In the conventional design, for the actual sample training, the sample selection object usually only selects the business samples that have passed the business verification, and then predicts the behavior of these business samples that have passed the business verification in the subsequent business use process. Those that have been ruled Or business samples rejected by the business forecasting model are usually excluded. The business forecasting model trained in this way cannot obtain the future behavior of those rejected business objects in the subsequent business forecasting, nor can it judge the various business indicators ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06K9/62G06N3/08G06N20/00G06F17/18G06Q10/06
CPCG06Q10/04G06N3/08G06N20/00G06F17/18G06Q10/06393G06F18/214G06Q10/06375G06Q10/067G06N5/01
Inventor 顾凌云谢旻旗段湾王震宇张阳
Owner SHANGHAI ICEKREDIT INC
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