Data mining method and device, computer equipment and storage medium

Abstract

The invention belongs to the field of artificial intelligence, and relates to a data mining method, which comprises the steps of extracting new features according to update data of a sample set; inputting the original modeling feature into a target model to obtain a first model output, dividing the sample set according to the first model output to obtain a plurality of sample partitions, and calculating a first evaluation parameter value of each sample partition; inputting the first model output and the new feature into a preset intermediate model to obtain a second model output, and calculating a second evaluation parameter value of each sample partition; and calculating evaluation parameter values of the new features according to the first evaluation parameter values and the second evaluation parameter values, and determining whether to take the new features as in-mold features of the target model or not according to the evaluation parameter values. The invention further provides a data mining device, computer equipment and a storage medium. The invention also relates to a block chain technology. The feature values of the new features determined as the in-mold features can be stored in the block chain. According to the method, the new features for improving the effect of the target model can be quickly selected, and the data mining efficiency is higher.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to data mining methods, devices, computer equipment and storage media. Background technique [0002] In data mining, feature analysis often uses IV (Information Value, information value or information volume) and correlation coefficient to judge the pros and cons of new features. The IV value can judge the correlation between a feature and the target variable, that is, its impact on the target variable. However, from the perspective of model effect, due to the redundancy of data information, high IV features may not necessarily improve the model effect. [0003] At present, in order to analyze the improvement of the model effect by the new features, the new features mined are added to the model one by one to see the model effect to judge the quality of the features. The problem with this operation is that the evaluation of new features takes a long time and...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present application is to propose a data mining method, device, computer equipment, and storage medium to solve the problems of long time-consuming and low efficiency in evaluating new features mined in the prior art

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