Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy

doi:10.3748/wjg.v28.i46.6551

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 28, Issue 46

This Article

Academic Content and Language Evaluation of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Number of Hits and Downloads for This Article

Total Article Views (6066)

All Articles published online

The chart showing PDF series, WORD series, HTML series, Figures (1-8) series, Tables (1-2) series.

Item

Count

PDF

300

WORD

HTML

3897

Figures (1-8)

411

Tables (1-2)

311

Sum=4973

Publishing Process of This Article

The chart showing Browse series, Download series.

Item

Count

Browse

360

Download

733

Sum=1093

Dec 14, 2022 (publication date) through Feb 8, 2025

Times Cited of This Article

Times Cited (27)

Journal Information of This Article

Publication Name

World Journal of Gastroenterology

ISSN

1007-9327

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Clinical and Translational Research

World J Gastroenterol. Dec 14, 2022; 28(46): 6551-6563
Published online Dec 14, 2022. doi: 10.3748/wjg.v28.i46.6551

Table 2 Result analysis

No.	Algorithm	Accuracy	AUC	Gini
1	CHAID model	71.36	0.746	0.493
2	CART model	73.24	0.724	0.448
3	Proposed model	93.55	0.987	0.974

AUC: Area under the curve; CART: Classification and regression tree; CHAID: Chi-square automated interaction detection.

Citation: Dalal S, Onyema EM, Malik A. Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy. World J Gastroenterol 2022; 28(46): 6551-6563
URL: https://www.wjgnet.com/1007-9327/full/v28/i46/6551.htm
DOI: https://dx.doi.org/10.3748/wjg.v28.i46.6551