A data classification method and apparatus

A data classification and data prediction technology, applied in the field of data processing, can solve the problems of ignoring random factors, lower classification efficiency, repeated and long algorithm logic structure, etc., and achieve the effect of clear classification logic structure

Inactive Publication Date: 2019-03-29
ZHENGZHOU YUNHAI INFORMATION TECH CO LTD
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The logic structure of the first algorithm is repetitive and long. For classification problems with many categories, the classification efficiency will be greatly reduced, which will affect the performance of the algorithm.
For the second method, the softmax regression method is adopted, but the random factors in the sample will be ignored

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A data classification method and apparatus
  • A data classification method and apparatus
  • A data classification method and apparatus

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] In order to make the objectives, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other arbitrarily if there is no conflict.

[0040] The steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than here.

[0041] figure 1 Is a flowchart of a data classification method according to an embodiment of the present invention, such as figure 1 As shown, the method of this embodiment may include:

[0042] Step 101: Determine the category probability of the predicted data set belonging to each category.

[0043...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a data classification method, which comprises the following steps: determining the probability that a prediction data set respectively belongs to each category; Constructing probability intervals belonging to each category of the prediction data set according to the probability; randomly generating a random number between [0, 1] is randomly generated, and determining a category of the prediction data set according to a probability interval in which the random number is located. A data classification apparatus is also disclosed. This scheme is mainly applied to the multi-class classification problem in machine learning field. This method not only enriches the internal logical structure of multi-class logistic regression algorithm, but also enhances the performance of multi-class logistic regression algorithm by judging the class and fully considering the influence of training sample error.

Description

Technical field [0001] The invention relates to data processing technology, in particular to a method and device for data classification. Background technique [0002] Multi-class logistic regression algorithms in machine learning generally have two logical structures. One is to establish a corresponding logistic (logical) classifier according to each category. The other is to improve the loss function of logistic regression to meet the needs of multiple classification problems. The logic structure of the first algorithm is repetitive and long. For classification problems with many categories, the classification efficiency will be greatly reduced, which will affect the performance of the algorithm. For the second method, the softmax regression method is adopted, but random factors in the sample will be ignored. Summary of the invention [0003] In order to solve the above technical problems, the present invention provides a method and device for data classification, which can fu...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/2415
Inventor 王文潇
Owner ZHENGZHOU YUNHAI INFORMATION TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products