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Evolutionary Intelligence

Erschienen in:

30.04.2020 | Special Issue

Construction of cascaded depth model based on boosting feature selection and classification

verfasst von: Hongwen Yan, Zhenyu Liu, Qingliang Cui

Erschienen in: Evolutionary Intelligence | Ausgabe 4/2022

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Abstract

Artificial intelligence is an important research direction in the field of computer science. Its vision is to better understand the world around us. In this paper, the specific feature transformation, feature selection and classifier algorithm used in the framework are studied and analyzed, and a cascade depth model is constructed. Through detailed analysis of the feature transformation, feature selection and classification methods used in the framework, an effective cascade depth model based on feature extraction and feature selection is successfully implemented, and the effectiveness of the proposed feature combination method is verified.

Vorheriger Artikel Neural multi-task collaborative filtering

Nächster Artikel Research and application of AHP-fuzzy comprehensive evaluation model

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Titel: Construction of cascaded depth model based on boosting feature selection and classification
verfasst von: Hongwen Yan
Zhenyu Liu
Qingliang Cui
Publikationsdatum: 30.04.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Evolutionary Intelligence / Ausgabe 4/2022
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI: https://doi.org/10.1007/s12065-020-00413-9

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