Input data processing method and device for categorical data mining model

Abstract

The invention discloses an input data processing method and device for a categorical data mining model. The method comprises the following steps: receiving data uploaded by a user, and carrying out preprocessing on the data; converting character type data in the data into numeric data; carrying out binning treatment on every continuous variable datum; calculating a preset index value of every variable, and screening a variable which is the most relevant to a preset target variable according to the preset index; and carrying out standardizing treatment on the data. Then operations such as datamodeling and follow-up classifying scoring can be carried out by treated data. Thus, after the data uploaded by the user are received, input data of the categorical data mining model can be processedautomatically, data analyzing personnel are not required, automation of a data processing stage in a data mining process is realized, moreover, operation is simple, and the operators do not need to have professional data analyzing experiences.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a method and device for processing input data of a classification data mining model. Background technique [0002] In recent years, with the development of big data technology, data mining technology has become increasingly mature. Data mining technology generally refers to the method of searching out hidden information from a large amount of data through algorithms. Data mining technology is widely used in many industries, such as: financial industry, communication industry, transportation industry, large retail and insurance industry and other industries. General data mining includes: data acquisition, data processing, model calculation, model online and other processes. However, in the traditional data mining process, the steps of data conversion, processing, inspection, and screening are mostly implemented by manual processing, which is inefficient and requires Professional da...

AI Technical Summary

Problems solved by technology

General data mining includes: data acquisition, data processing, model calculation, model online and other processes. However, in the traditional data mining process, the steps of data conversion, processing, inspection, and screening are mostly realized by manual processing, which is inefficient and requires Professional data analysts are involved

[0003] In the prior art, although some data mining tools are included, such as Python, SAS, etc., these software require very professional knowledge, and the popularity is low.

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