Confidence regression algorithm and device based on KNN (K-Nearest-Neighbor)

A regression algorithm, regression value technology, applied in the field of machine learning, can solve the problem of inaccurate confidence regression

Inactive Publication Date: 2015-04-22
SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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Problems solved by technology

[0006] The purpose of the embodiments of the present invention is to provide a confidence regression algorithm based on KNN, which solves the problem of inaccurate confidence regression in the prior art

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  • Confidence regression algorithm and device based on KNN (K-Nearest-Neighbor)
  • Confidence regression algorithm and device based on KNN (K-Nearest-Neighbor)
  • Confidence regression algorithm and device based on KNN (K-Nearest-Neighbor)

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[0028] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0029] The specific embodiment of the present invention provides a kind of confidence regression algorithm based on KNN, and the above-mentioned method is carried out by the confidence machine, and this method is as follows figure 1 shown, including the following steps:

[0030] 101. Determine a sample set, the sample set includes: a known regression sample set and an unknown regression sample set;

[0031] 102. Select the unknown sample x from the unknown regression sample set p ;

[0032] 103. Calculate x p The Euclidean distance D between each sample in the known regression sample set E ...

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Abstract

The invention is applicable to the field of machine learning and provides a confidence regression algorithm based on KNN (K-Nearest-Neighbor). The confidence regression algorithm comprises the following steps: determining a sample set, wherein the sample set comprises a known regression sample set and an unknown regression sample set; selecting an unknown sample from the unknown regression sample set and calculating an Euclidean distance between the unknown sample and each sample in the known regression sample set; inquiring K samples with the Euclidean distances which are the closest to the unknown sample from the known regression sample set; calculating an average value of regression values of the K samples; predicating a regression value of the unknown sample by a regression module; calculating a difference value T between the regression value and the average value; and dividing an acceptance domain and a rejection domain according to the difference value T. The confidence regression algorithm based on the KNN has the advantage that the regression value is accurate.

Description

technical field [0001] The invention belongs to the field of machine learning, and in particular relates to a KNN-based confidence regression algorithm and device. Background technique [0002] In addition to the research on classification problems in the field of machine learning, another important research field is the research on regression prediction. Therefore, corresponding to confidence machine learning research, it should also include confidence classification research and confidence regression research. At present, the research on confidence machine learning mainly focuses on classification problems, and most of the current research on confidence machines mainly focuses on confidence classification problems, while the research on confidence regression is relatively small; however, confidence regression is used in high-risk applications such as medical diagnosis and prediction. field has important practical significance. [0003] A kind of support vector machine me...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06F19/24
Inventor 蒋方纯田盛丰
Owner SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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