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Data evaluation method and device, terminal equipment and storage medium

A technology for evaluating devices and data, applied in the computer field, can solve problems such as low efficiency and low accuracy, and achieve the effects of improving efficiency, improving accuracy, and avoiding tediousness and uncertainty.

Pending Publication Date: 2018-11-02
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] Embodiments of the present invention provide a data evaluation method, device, terminal equipment, and storage medium to solve the problem of low efficiency and low accuracy caused by manual evaluation of data

Method used

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  • Data evaluation method and device, terminal equipment and storage medium
  • Data evaluation method and device, terminal equipment and storage medium
  • Data evaluation method and device, terminal equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] see figure 1 , figure 1 The implementation flow of the data evaluation method provided in this embodiment is shown. The details are as follows:

[0031] S1: Preprocess the sample variables in the sample data set to obtain the nominal variables sorted by the size of the eigenvalues.

[0032] Specifically, the sample variables in the sample data set are the attribute characteristics of the sample data, such as age, income, and gender. The sample variables include continuous variables and discrete variables. According to the type of sample variables, the specific preprocessing methods can refer to the following examples Note that for continuous variables, the proposed splitting point is performed according to the preset proposed splitting point, and the difference between the information gain before the proposed splitting and after the proposed splitting is calculated. If the difference exceeds the preset threshold, the proposed splitting point is considered as the split...

Embodiment 2

[0132] Corresponding to the data evaluation method in Example 1, Figure 8 The data evaluation device corresponding to the data evaluation method provided in Embodiment 1 is shown, and for the convenience of description, only the parts related to the embodiment of the present invention are shown.

[0133] Such as Figure 8 As shown, the data evaluation device includes: a sample variable preprocessing module 10 , a digitized variable acquisition module 20 , a decision tree model generation module 30 and a preset event result prediction module 40 . The detailed description of each functional module is as follows:

[0134] The sample variable preprocessing module 10 is used to preprocess the sample variables in the sample data set to obtain nominal variables sorted according to the size of the eigenvalues;

[0135] The digitized variable acquisition module 20 is used to perform one-hot encoding on the nominal variable, and convert the nominal variable into a digitized variable;...

Embodiment 3

[0160] This embodiment provides a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, the data evaluation method in Embodiment 1 is implemented, or, when the computer program is executed by the processor, Realize the functions of each module / unit in the data evaluation device in Embodiment 2. To avoid repetition, details are not repeated here.

[0161] It can be understood that the computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (Read- Only Memory, ROM), random access memory (Random Access Memory, RAM), electric carrier signal and telecommunication signal, etc.

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Abstract

The invention discloses a data evaluation method and device, terminal equipment and a storage medium. The method comprises the following steps of carrying out preprocessing on sample variables in a sample data set in order to obtain nominal variables which are ordered according to the sizes of characteristic values; carrying out one-hot coding on the nominal variables which are ordered according to the sizes of the characteristic values, and converting the nominal variables into digital variables; applying a gradient lifting decision-making tree algorithm to the sample data set containing thedigital variables; generating a decision tree model comprising n decision trees; and acquiring combined characteristics by adopting the gradient lifting decision-making tree algorithm. The accuracy ofprediction of the combined characteristics of sample data is improved, and the efficiency of acquisition of the combined characteristics is also improved, so that the combined characteristics are used as input characteristics of a binary logic regression model to carry out prediction of a preset event result, and thus the complexity and the uncertainty of manual searching of the characteristics are avoided, the prediction accuracy of the sample data for the preset event result is improved, and meanwhile, the accuracy and the efficiency of sample data evaluation are also improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a data evaluation method, device, terminal equipment and storage medium. Background technique [0002] In real life, we need to predict many things, such as: future housing price trends, weather changes, etc. When predicting these things, it is often necessary to collect a large amount of sample data, and then through manual analysis, find out which of these sample data The necessary features related to the preset event, and assign a certain weight value to each necessary feature, and then calculate the probability of various outcomes of the preset event according to the feature values ​​of these artificially weighted features, so as to evaluate the sample data. The impact of preset events. [0003] However, with the rapid development of science and technology, the sample data is getting larger and larger. It takes a lot of time to analyze the data manually to select t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/18
CPCG06F17/18
Inventor 黄严汉曾凡刚
Owner CHINA PING AN LIFE INSURANCE CO LTD
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