A data dimensionality reduction method

A data dimension reduction and high-dimensional data technology, applied in the field of data processing, can solve problems such as the inability to analyze massive data, achieve the effect of improving operating efficiency and reducing the calculation process

Inactive Publication Date: 2019-01-11
GUANGDONG POWER GRID CO LTD +1
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Problems solved by technology

Traditional data processing methods have been unable to effectively analyze massive data

Method used

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  • A data dimensionality reduction method

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Embodiment Construction

[0036] In order to make the purpose, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the following The described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0037] see figure 1 As shown, this embodiment provides a method for data dimensionality reduction, which specifically includes the following steps:

[0038] Step S1: Preprocessing the high-dimensional data to obtain a high-dimensional data set, and selecting a kernel function;

[0039] Step S2: Construct a global objective function based ...

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Abstract

The invention discloses a data dimensionality reduction method, which comprises the following steps: preprocessing the high-dimensional data to obtain a high-dimensional data set, and selecting a kernel function; constructing a global objective function based on kernel principal component analysis and solving the kernel matrix; adaptively adjusting the neighborhood parameter value and constructingthe local objective function by local preserving projection method; determining a balance factor value to balance the global objective function and the local objective function, and combining the global objective function and the local objective function into an overall objective function; determining the number of principal components and the projection matrix, and multiplying the projection matrix and the high-dimensional data set to obtain a low-dimensional data set. The data dimensionality reduction method provided by the embodiment of the invention, based on the kernel principal component analysis and the local preservation projection method, can remove noise and redundant information in a high-dimensional data set, reduce unnecessary operation process in data mining, and improve theoperation efficiency of the algorithm.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a data dimensionality reduction method. Background technique [0002] With the vigorous development of power communication networks, the volume of power communication data is increasing. Traditional data processing methods have been unable to effectively analyze massive data. At the same time, as the data dimensions generated by power communication networks, big data processing, and cloud computing continue to increase, in order to remove noise and redundant information in high-dimensional data sets, reduce unnecessary calculations in data mining, and improve the performance of algorithms It is also more necessary to reduce the dimensionality of high-dimensional data to improve operational efficiency. [0003] Data dimensionality reduction maps data sets from high-dimensional space to low-dimensional space through a certain mapping relationship, and extracts the main fe...

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Application Information

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IPC IPC(8): G06F16/215
Inventor 李星南曾瑛林斌付佳佳施展吴赞红
Owner GUANGDONG POWER GRID CO LTD
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