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
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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

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  • 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

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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...

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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

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Application Information

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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
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