Unlock instant, AI-driven research and patent intelligence for your innovation.

Method for classifying big data based on confusion matrix

A confusion matrix and big data technology, applied in the field of information, to achieve the effect of improving classification accuracy, speeding up calculation analysis, and accurate classification

Inactive Publication Date: 2017-11-24
NAT UNIV OF DEFENSE TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The technical problem to be solved by the present invention is to propose a method for classifying big data based on confusion matrix to improve the accuracy of big data classification and speed up big Computational Analysis of Data

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
  • Method for classifying big data based on confusion matrix
  • Method for classifying big data based on confusion matrix
  • Method for classifying big data based on confusion matrix

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0074] Define sample dyads as follows:

[0075] d 11 =

[0076] d 12 =

[0077] d 13 =

[0078] d 21 =

[0079] d 22 =

[0080] d 23 =

[0081] d 31 =

[0082] d 32 =

[0083] d 33 =

[0084] Among them: pixel represents the pixel feature, color represents the color feature, sound represents the sound feature, image represents the moving image feature, texture represents the texture feature, and MB|GB represents the different magnitudes of the size feature.

[0085] 3.2.1. Define variable i=1;

[0086] 3.2.2. Define variable j=1;

[0087] 3.2.3. Define variable i'=1;

[0088] 3.2.4. Define variable j'=1;

[0089] 3.2.5. Judgment sample d 11 Is it with D 1 Similarly, the steps are as follows:

[0090] 3.2.5.1.num(K 1 )≠num(K 1 ), sample d ij with D i' Different types, go to 3.2.5.8, otherwise, go to 3.2.5.2;

[0091] 3.2.5.2.K i ≠ K i' , representing the set K i with K i' Different, it is necessary to judge the similarity, go to 3.2.5.3, otherwise,...

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 method for classifying big data based on a confusion matrix and aims to solve the problem that a large amount of data noise is hidden while high-value information is contained during big data mining so as to improve big data classification accuracy to accelerate calculation and analysis of the big data. According to the technical scheme, first, data category rough classification is performed on the big data to obtain a big data set D; second, the total number TN of samples in D is subjected to statistical analysis, and a D-oriented classification judgment confusion matrix P is constructed; and last, D-oriented classification accuracy OA and classification effective accuracy EA are calculated, and OA and EA are output. By the adoption of the method, big data classification accuracy can be improved, and calculation, analysis and other processing processes of the big data can be accelerated.

Description

technical field [0001] The invention relates to a classification method, in particular to a method for classifying large data based on a confusion matrix in the information field. Background technique [0002] As a very important task in data mining, data classification is widely used in business, military and scientific research decision analysis. With the continuous advancement of social informatization, the amount of global digital information has grown rapidly in the past five years, from the previous TB level to the PB level, or even the EB level. With the continuous increase of data scale and data volume, the scale of data classification problems in the era of big data is getting larger and larger, and the number of samples, feature dimensions, and categories are all increasing rapidly. A large amount of data noise, therefore, how to determine the accuracy of big data classification in big data classification is the key technology to accurately extract the value of bi...

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
IPC IPC(8): G06K9/62G06F17/16
CPCG06F17/16G06F18/24
Inventor 甘新标刘杰徐涵胡庆丰晏益慧龚春叶李胜国邹丹熊成伟黄嘉昆
Owner NAT UNIV OF DEFENSE TECH