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Method and device for extracting dimensionality reduction features

A dimensionality reduction and importance technology, applied in character and pattern recognition, instruments, computing, etc., can solve the problem of difficult to obtain label data, and achieve the effect of improving prediction performance

Active Publication Date: 2021-05-28
北京互金新融科技有限公司
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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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Embodiment Construction

[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 present application discloses a method and device for extracting dimensionality reduction features. The method includes: extracting a feature importance value in a preset scene from the training data, wherein the training data is labeled structured data, and the feature importance value is used to indicate the degree of influence of the feature on the result identified in the label; Normalize the feature importance value to obtain the feature importance vector; pass the feature importance vector to the sparse autoencoder network to affect the neuron weight; input unlabeled structured data into the sparse autoencoder network, to perform dimensionality reduction on unlabeled structured data. Through this application, it solves the technical problem that it is difficult to obtain labeled data 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 cannot meet the current needs.

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 Patents(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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