Model feature screening method and device and readable storage medium

A feature screening and model technology, applied in the field of machine learning, can solve problems such as the inability to accurately screen model features, and achieve the effect of improving accuracy

Inactive Publication Date: 2019-10-29
上海上湖信息技术有限公司
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Problems solved by technology

[0005] The embodiment of the present invention solves the technical problem that effective model features cannot be accurately screened out

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  • Model feature screening method and device and readable storage medium

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Embodiment Construction

[0024] In the prior art, in the pattern recognition problem, the basic task of feature selection is how to find out the most effective features from many features, analyze the effectiveness of various features and select the most representative features. Existing feature selection methods include: remove feature selection methods with small value changes, univariate feature selection methods, Pearson correlation coefficient selection methods, and distance correlation coefficient selection methods, etc. However, none of the above methods can solve specific pattern recognition problems. Perform accurate feature selection.

[0025]In the embodiment of the present invention, step 1, using the i-th group of candidate features to establish the corresponding i-th model; i is greater than or equal to 1; step 2, performing model interpretation on the i-th model to obtain the i-th group of candidate features The feature contribution corresponding to each feature in ; step 3, according t...

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Abstract

The invention discloses a model feature screening method and device and a readable storage medium. The model feature screening method comprises the following steps: step 1, establishing a corresponding ith model by adopting an ith group of candidate features, wherein i is greater than or equal to 1; step 2, carrying out model interpretation on the ith model to obtain a feature contribution corresponding to each feature in the ith group of candidate features; step 3, screening the i-th group of candidate features according to the feature contribution corresponding to each feature, and excludingfeatures which do not meet a preset condition to obtain an i + 1-th group of candidate features; and step 4, taking the (i + 1) th group of candidate features as the ith group of candidate features,and repeatedly executing the step 1 to the step 3 until all the features which do not meet the preset condition are excluded to obtain target features. By adopting the scheme, effective model featurescan be accurately screened out.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to a model feature screening method and device, and a readable storage medium. Background technique [0002] Feature Selection is also called Feature Subset Selection (FSS), or Attribute Selection. Feature selection refers to the selection of N features from the existing M features (Feature) to optimize the specific indicators of the system. It is the process of selecting some of the most effective features from the original features to reduce the dimension of the data set. It is the process of improving the learning algorithm. It is an important means of performance and also a key data preprocessing step in pattern recognition. For a learning algorithm, good learning samples are the key to training the model. [0003] For example, in the field of financial risk identification, feature extraction is a very critical link in credit risk modeling. Effective and ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06Q40/02
CPCG06N3/08G06Q40/03
Inventor 赵劼铖张俊
Owner 上海上湖信息技术有限公司
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