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xgboost learner node  (KNIME GmbH)
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KNIME GmbH xgboost learner node
The accuracy of predicting the severity of side effects after receiving different COVID-19 vaccines using different ML tools based on the demographic data and other participant responses.
Xgboost Learner Node, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/xgboost+learner+node/xgboost+learner+node/pmc08229440-291-3-7
Average 90 stars, based on 1 article reviews
xgboost learner node - by Bioz Stars, 2026-10
90/100 stars
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The accuracy of predicting the severity of side effects after receiving different COVID-19 vaccines using different ML tools based on the demographic data and other participant responses.

Journal: Vaccines

Article Title: Side Effects and Perceptions Following COVID-19 Vaccination in Jordan: A Randomized, Cross-Sectional Study Implementing Machine Learning for Predicting Severity of Side Effects

doi: 10.3390/vaccines9060556

Figure Lengend Snippet: The accuracy of predicting the severity of side effects after receiving different COVID-19 vaccines using different ML tools based on the demographic data and other participant responses.

Article Snippet: We implemented the XGBoost learner node within KNIME Analytics Platform with the following settings: tree booster was implemented with depth wise grow policy, boosting rounds = 100, Eta = 0.3, Gamma = 0, maximum depth = 6, minimum child weight = 1, maximum delta step = 0, subsampling rate = 1, column sampling rate by tree = 1, column sampling rate by level = 1, lambda = 1, Alpha = 0, sketch epsilon = 0.03, scaled position weight = 1, maximum number of bins = 256, sample type (uniform), normalize type (tree), and dropout rate = 0.

Techniques: Vaccines