Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Confidence evaluation method, system and equipment in big data analysis based on support vector machine, and storage medium

A technology of support vector machine and evaluation method, applied in the direction of kernel method, data processing application, computer parts, etc., can solve the problems of inability to achieve quantitative and intuitive measurement, fault-tolerant correction, inability to directly provide confidence evaluation method, etc., to achieve accurate Classification confidence evaluation, the effect of intuitive classification

Pending Publication Date: 2021-12-10
NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT +1
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Most and machine learning algorithms cannot directly provide confidence evaluation methods, and cannot achieve quantitative and intuitive measurements. What is more provided is label marks, and the classification results have been determined. In this case, it is impossible to combine more Algorithms for data filtering, and fault-tolerant corrections for identified classifications

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
  • Confidence evaluation method, system and equipment in big data analysis based on support vector machine, and storage medium
  • Confidence evaluation method, system and equipment in big data analysis based on support vector machine, and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] Such as figure 1 and figure 2 As shown, it is a high-availability confidence evaluation method based on a support vector machine in this embodiment, including the following steps:

[0033] (1) Preprocess massive data and perform standardized data input.

[0034] (2) Select the call success rate, the rate of ringing and early release, the proportion of call duration less than 10s, the proportion of called numbers with only one connection in total, the geographical dispersion of called numbers, whether they are 001+area code numbers, etc. Dimensions, select machine learning feature dimensions, and form feature vectors to prepare for subsequent model training.

[0035] (3) Determine the classification label, and associate the label with the feature vector to form a label-feature vector.

[0036] (4) The label-feature vector is used as input, and the model training is carried out through the support vector machine algorithm to obtain a hyperplane classification model, a...

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 confidence evaluation method and a system in big data analysis based on a support vector machine, which are applied to the field of analysis of internet crank calls and are used for evaluating the crank calls. According to the method, confidence evaluation of automatic classification is realized based on the support vector machine, and a solution of classification evaluation in the field of mass data analysis is provided, so that crank calls are efficiently and intuitively classified. According to the method, efficient and accurate classification confidence evaluation is performed on the analysis sample.

Description

technical field [0001] The present invention is applied to the analysis field of Internet harassing calls, relates to the field of big data processing and analysis, combined with machine learning improvement methods, especially a method for evaluating and classifying typical data features in the process of big data analysis. Background technique [0002] In recent years, with the rapid development of the mobile Internet, the penetration rate of smart terminals has been increasing year by year, the frequency of Internet harassment calls has also increased sharply, and the means of purifying the network environment have also been gradually improved. On the basis of massive data, various Data analysis evaluation models and classification models have also emerged as the times require. [0003] In the traditional machine learning method, because the support vector machine-SVM has a good classification effect and has good "robustness", it basically does not involve the law of larg...

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): G06K9/62G06Q10/06G06N20/10
CPCG06Q10/06393G06N20/10G06F18/214
Inventor 李扬曦王佩刘科栋彭成维肖林焱王亚箭黄自强
Owner NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com