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An employee evaluation method and terminal equipment based on a classification prediction model

A prediction model and classification prediction technology, applied in the field of data processing, can solve problems such as low accuracy and low efficiency of candidate employee identification, and achieve the effect of improving accuracy and efficiency

Pending Publication Date: 2019-02-15
CHINA PING AN LIFE INSURANCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, an embodiment of the present invention provides an employee evaluation method and terminal device based on a classification prediction model to solve the problem of low efficiency and low accuracy in identifying candidates with high potential among candidate employees in the prior art. question

Method used

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  • An employee evaluation method and terminal equipment based on a classification prediction model
  • An employee evaluation method and terminal equipment based on a classification prediction model
  • An employee evaluation method and terminal equipment based on a classification prediction model

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Embodiment 2

[0044] As a specific implementation of the first prediction model training in Embodiment 1 of the present invention, considering that the index assessment results and promotion evaluation results in the evaluation data are directly used to construct the prediction model training, the accuracy of the final prediction model is difficult to obtain. is well guaranteed, so in order to ensure the accuracy and effectiveness of the final prediction model, such as figure 2 As shown, Embodiment 2 of the present invention includes:

[0045] S201. Obtain the assessment time period of the promotion assessment process corresponding to each set of assessment data in the first assessment data set.

[0046] Since the promotion evaluation is based on whether the index evaluation results of the employees in the evaluation time period meet the index requirements, therefore, each promotion evaluation process must correspond to an evaluation time period, for example, from January 2017 to March 201...

Embodiment 3

[0052] As a specific implementation of the second prediction model training in Embodiment 1 of the present invention, considering that the index assessment results and promotion evaluation results in the evaluation data are directly used to construct the prediction model training, the accuracy of the final prediction model is difficult to obtain. is well guaranteed, so in order to ensure the accuracy and effectiveness of the final prediction model, such as image 3 As shown, the third embodiment of the present invention includes:

[0053] S301. Acquire the evaluation time period of the promotion evaluation process corresponding to each group of evaluation data in the second evaluation data set.

[0054] S302, for each employee corresponding to the second assessment data set, analyze the data change trend of the index assessment results in all the corresponding assessment data within the corresponding assessment time period, and obtain the unique second change trend score corre...

Embodiment 4

[0060] As a specific implementation of data change trend analysis in Embodiment 2 of the present invention and Embodiment 3 of the present invention, as Figure 4 As shown, Embodiment 4 of the present invention includes:

[0061] S401. Obtain multiple assessment time nodes included in the assessment time period, and split the index assessment results into assessment results that correspond one-to-one to the multiple assessment time nodes.

[0062] S402, performing linear function fitting on the assessment result, and using the slope value of the fitted linear function as the corresponding change trend score.

[0063] The assessment time node refers to each time period after the assessment time period is divided into multiple time periods of equal length. The specific time period division rules can be set by the technician according to the actual situation. For example, the employee performance data assessment time period is From January to March, at this time, the assessment ...

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Abstract

The invention provides an employee evaluation method and a terminal device based on a classification prediction model, which are applicable to the technical field of data processing. The method comprises the following steps: obtaining the evaluation data of a plurality of employees to form a first evaluation data set; the employees are employees whose grade before evaluation and evaluation targetgrade are the same as those of candidate employees in the promotion evaluation process; Screening out from the first evaluation data set the evaluation data corresponding to the same employee whose group number is greater than 1 to form a second evaluation data set; Training a first prediction model based on the first evaluation data set and training a second prediction model based on the second evaluation data set; Based on the trained first prediction model and the trained second prediction model, the evaluation data of the candidate employees are processed to obtain the evaluation results of the corresponding candidate employees. The embodiment of the invention simultaneously evaluates the candidate staff from different dimensions to determine the probability of success of the next promotion, thereby greatly improving the accuracy and efficiency of the evaluation of the candidate staff.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to an employee evaluation method and terminal equipment based on a classification prediction model. Background technique [0002] There are a lot of employees in the enterprise who need to evaluate the promotion of position grades. Each promotion evaluation needs to process the index evaluation results within the evaluation time period corresponding to the promotion evaluation of employees this time, and judge whether the index evaluation results meet the corresponding index requirements of the employee evaluation target level. To determine whether an employee can be successfully promoted from the pre-assessment level to the assessment target level, such as processing the performance data of each month from January to March during the employee assessment period, and judging whether the employee's performance data during the assessment period meets the requirements...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/04G06K9/62
CPCG06Q10/04G06Q10/06398G06F18/214
Inventor 高勇陈战仁许进
Owner CHINA PING AN LIFE INSURANCE CO LTD