INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The study contains fundamental details about the XGBoost Machine Learning Approach of Classification. The discussion of the XGBoost algorithm and its comparison with other Classification algorithms, such as Gradient Boosting and Random Forest algorithm, which are used to address a variety of prediction and recommendation-related real-world problems, was more broadly covered. The XGBoost algorithm, its features, and the workings of its techniques, which are used in recommendation systems, were the paper's primary topics. These algorithms' goals, features, and comparison to other classification algorithms are all described in detail.
Keywords:
Machine Learning, Tree Algorithms, Tree Boosting, Random Forest, XGBoost, LightGBM, CatBoost
Cite Article:
"XGBoost Algorithm and its Comparative Analysis", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 12, page no.b892-b895, December-2022, Available :http://www.ijnrd.org/papers/IJNRD2212198.pdf
Downloads:
000118747
ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Facebook Twitter Instagram LinkedIn