Results 41 to 50 of about 7,127,658 (298)

The determinants of health assessment in the United States: A supervised learning approach

Healthcare Analytics, 2022
In this article, we exploit a large dataset of surveys to answer a simple questions: which factors drive good (or bad) health? Using a set of 14 very diverse predictors (both socioeconomic and physiological), we perform sets of supervised learning tasks ...
Guillaume Coqueret
doaj   +1 more source

Feature importance ranking from RF.

, 2022
Feature importance ranking from RF.
Yuge Li (13511948), Ruxu Du (4558435), Jinyang Du (11175324), Guiyuan Peng (13767117), Yong Zhong (464992), Qi Liu (33068), Xuefang Wang (215231)   +6 more
core   +1 more source

Forecasting Coronary Heart Disease Risk With a 2-Step Hybrid Ensemble Learning Method and Forward Feature Selection Algorithm

IEEE Access, 2023
Detecting cardiovascular irregularities in a timely manner is crucial for preventing any fatal risks. This research aims to devise an efficient forecasting algorithm for the timely prognosis of Coronary Heart Disease (CHD).
Sushree Chinmayee Patra, B. Uma Maheswari, Peeta Basa Pati   +2 more
doaj   +1 more source

Features Importance

, 2021
Features importances and sensor ...
openaire   +1 more source

Feature selection for modular GA-based classification [PDF]

, 2004
Genetic algorithms (GAs) have been used as conventional methods for classifiers to adaptively evolve solutions for classification problems. Feature selection plays an important role in finding relevant features in classification.
Guan, SU, Zhu, F, Zhu, F., Guan, S.
core   +1 more source

Feature importance (Importance) and p values for features that achieved a feature importance greater than 0.1% in the Japanese RF.

, 2023
Feature importance (Importance) and p values for features that achieved a feature importance greater than 0.1% in the Japanese RF.
Shigeto Kawahara (3183039), Alexander James Kilpatrick (14328725), Aleksandra Ćwiek (14328728)   +2 more
core   +1 more source

The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach

Frontiers in Big Data
IntroductionStudies from different parts of the world have shown that some comorbidities are associated with fatal cases of COVID-19. However, the prevalence rates of comorbidities are different around the world, therefore, their contribution to COVID-19
Jorge Méndez-Astudillo
doaj   +1 more source

A Feature Selection Method for Multi-Label Text Based on Feature Importance

Applied Sciences, 2019
Multi-label text classification refers to a text divided into multiple categories simultaneously, which corresponds to a text associated with multiple topics in the real world.
Lu Zhang, Qingling Duan
doaj   +1 more source

Disentangled Feature Importance

CoRR
29 main and 44 supplementary ...
Jin-Hong Du, Kathryn Roeder, Larry A. Wasserman   +2 more
openaire   +2 more sources

Relative feature importance.

, 2018
Normalized average relative feature importance for both learning methods (RF and GBM) for all included networks. For each model we quantified relative importance by a weight between 0 and 1 for each feature.
Polonca Ferk (5184017), Brane Leskošek (5184020), Andrej Kastrin (595224)   +2 more
core   +1 more source