Method and device for extracting dimensionality reduction features

A dimension reduction and importance technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problem of difficult access to label data

Active Publication Date: 2019-09-06
北京互金新融科技有限公司
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  • Application Information

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Problems solved by technology

[0008] This application provides a method and device for extracting dimensionality reduction features to solve the problem that labeled data is difficult to obtain in related technologies, and none of the existing solutions for extracting effective information from unlabeled data to improve the model prediction performance of the scene Technical issues that meet today's needs

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  • Method and device for extracting dimensionality reduction features
  • Method and device for extracting dimensionality reduction features
  • Method and device for extracting dimensionality reduction features

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[0029] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0031] It should be noted that the terms "first" and "second...

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Abstract

The invention discloses a method and device for extracting dimensionality reduction features. The method comprises the steps: extracting feature importance values under a preset scene from training data, wherein the training data are structured data with labels, and the feature importance values are used for indicating the degree of influence of the features on identification results in the labels; performing normalization processing on the feature importance values to obtain feature importance vectors; transmitting the feature importance vector to a sparse self-coding network to influence theweight of a neuron; and inputting the unlabeled structured data into a sparse self-coding network so as to carry out dimension reduction processing on the unlabeled structured data. Through the method and device, the technical problem that in the related art, labeled data are difficult to obtain, and an existing scheme for extracting effective information from unlabeled data to improve the modelprediction performance of the scene cannot meet the current requirement is solved.

Description

technical field [0001] The present application relates to the field of feature extraction, in particular, to a method and device for extracting dimensionality reduction features. Background technique [0002] In machine learning modeling scenarios, there will be a shortage of labeled data but a large amount of unlabeled data. In this case, if only a small amount of labeled data is used for modeling, good prediction results are often not obtained. For example, in the field of financial consumer credit, cashing out of orders often occurs, but the acquisition of such tag data requires relatively high costs in terms of time and labor costs. [0003] The current method to deal with this small number of samples is to use sample generation methods to increase the sample size, but this method is prone to over-fitting in the modeling process. [0004] In the case that the above-mentioned labeled data is difficult to obtain, effective information can be extracted from unlabeled data...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/2136G06F18/2155
Inventor 高树立
Owner 北京互金新融科技有限公司
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