An Advanced Hybrid Logistic Regression Model for Static and Dynamic Mixed Data Classification-Reference-Cited by-同舟云学术

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An Advanced Hybrid Logistic Regression Model for Static and Dynamic Mixed Data Classification

Published:2022 Issue: Volume:10 Page:73623-73634
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Quan Mingxue¹^ORCID

Affiliation:

1. School of Mathematics, Renmin University of China, Beijing, China

Funder

Educational Research Projects of Young and Middle-Aged Teachers in Fujian Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09812627.pdf?arnumber=9812627

Reference50 articles.

1. Mixed data analysis: Advanced integration techniques

2. Functional logistic regression: a comparison of three methods

3. Combining Static and Dynamic Features for Multivariate Sequence Classification

4. Distance between populations using mixed continuous and categorical variables

5. Functional logistic regression with fused lasso penalty

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