Subsequently, we incorporated statistically significant variables from the chi-square test into a binary logistic regression analysis model and a categorical decision tree model to identify the main ...

In this study, we attempt to leverage the ability of supervised learning methods, such as ANNs, KANs, and gradient-boosted decision trees, to approximate complex multivariate functions in order to ...

In this video, we will learn what is linear regression in machine learning along with examples to make the concept crystal clear.

Moreover, the present decision tree algorithm identified more and different variables related to SLD than those reported in the current definition of MASLD. It is worth noting that the regression tree ...

Regression trees are applied to evaluate system performance – using two water quality and two economic performance metrics. Regression trees facilitated insights into the significance of uncertain ...

Welcome to the online version of From the Politics Desk, an evening newsletter that brings you the NBC News Politics team’s latest reporting and analysis from the White House, Capitol Hill and ...

Lung cancer is one of the most deadly and ubiquitous forms of cancer globally. Early detection can make a significant difference in survival rates, prognosis, etc. Background The present study ...

To achieve the purpose of improving rehabilitation effect and quality of life, this study combining decision trees with logistic regression models was of high value in studying factors influencing ...

Decision tree regression is a fundamental technique that can be used by itself, and is also the basis for powerful ensemble techniques (a collection of many decision trees), notably, AdaBoost ...