Research and application of XGBoost in imbalanced data
As a new and efficient ensemble learning algorithm, XGBoost has been widely applied for its multitudinous advantages, but its classification effect in the case of data imbalance is often not ideal. Aiming at this problem, an attempt was made to optimize the regularization term of XGBoost, and a clas...
Main Authors: | Ping Zhang, Yiqiao Jia, Youlin Shang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-06-01
|
Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/15501329221106935 |
Similar Items
-
Influence-Balanced XGBoost: Improving XGBoost for Imbalanced Data Using Influence Functions
by: Akiyoshi Sutou, et al.
Published: (2024-01-01) -
XGBoost for Imbalanced Data Based on Cost-sensitive Activation Function
by: LI Jing-tai, WANG Xiao-dan
Published: (2022-05-01) -
An Effective Cost-Sensitive XGBoost Method for Malicious URLs Detection in Imbalanced Dataset
by: Shen He, et al.
Published: (2021-01-01) -
Solving the Imbalanced and Limited Data Labeled for
Automated Essay Scoring using Cost Sensitive
XGBoost and Pseudo-Labeling
by: Pramularsih, Marvina, et al.
Published: (2022) -
Research on Processing and Application of Imbalanced Textual Data on Social Platforms
by: JIANG Yuqi, HOU Zhiwen, WANG Yifan, ZHAI Hanming, BU Fanliang
Published: (2024-09-01)