A feature selection algorithm of decision tree based on feature weight
HF Zhou, JW Zhang, YQ Zhou, XJ Guo… - Expert Systems with …, 2021 - Elsevier
In order to improve the classification accuracy, a preprocessing step is used to pre-filter
some redundant or irrelevant features before decision tree construction. And a new feature …
some redundant or irrelevant features before decision tree construction. And a new feature …
Accuracy and diversity-aware multi-objective approach for random forest construction
NEI Karabadji, AA Korba, A Assi, H Seridi… - Expert Systems with …, 2023 - Elsevier
Random Forest is an ensemble classification approach. It aims to design a discrete finite
group of decision trees constructed based on bootstrap samples and random attribute …
group of decision trees constructed based on bootstrap samples and random attribute …
Modeling uncertain data using Monte Carlo integration method for clustering
Nowadays, data clustering is an important task to the mining research community since the
availability of uncertain data is increasing rapidly in many applications such as weather …
availability of uncertain data is increasing rapidly in many applications such as weather …
A preordonance-based decision tree method and its parallel implementation in the framework of Map-Reduce
In supervised classification, decision trees are one of the most popular learning algorithms
that are employed in many practical applications because of their simplicity, adaptability …
that are employed in many practical applications because of their simplicity, adaptability …
Machine and deep learning algorithms for wearable health monitoring
Because people desire a high quality of life, health is a vital standard of living factor that is
attracting considerable attention. Thus, the development of methods that enable rapid and …
attracting considerable attention. Thus, the development of methods that enable rapid and …
[HTML][HTML] State-of-the-art methods in healthcare text classification system: AI paradigm
Machine learning has shown its importance in delivering healthcare solutions and
revolutionizing the future of filtering huge amountd of textual content. The machine …
revolutionizing the future of filtering huge amountd of textual content. The machine …
ZTEI: Zero-trust and edge intelligence empowered continuous authentication for satellite networks
P Fu, J Wu, X Lin, A Shen - GLOBECOM 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
The integration of satellite communication technology and terrestrial infrastructure has
resulted in an un-precedented increase in network services covering the world. The main …
resulted in an un-precedented increase in network services covering the world. The main …
Fault diagnosis of rolling bearing based on the permutation entropy of VMD and decision tree
X Chen, Z Yang, W Lou - 2019 3rd International Conference on …, 2019 - ieeexplore.ieee.org
Rolling bearing is the most important component of rotating machinery. The research of the
fault diagnosis of rolling bearing can effectively improve the running reliability of rotating …
fault diagnosis of rolling bearing can effectively improve the running reliability of rotating …
Analysis of the prediction performance of decision tree-based algorithms
Due to their many benefits, decision trees are extensively utilized to solve a variety of
classification problems in the real world. Consequently, creating efficient and effective …
classification problems in the real world. Consequently, creating efficient and effective …
Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning
Z Yang, X Guo, X Chen, J Huang - Plos one, 2024 - journals.plos.org
This study investigates the impact of maternal health on infant development by developing a
mathematical model that delineates the relationship between maternal health indicators and …
mathematical model that delineates the relationship between maternal health indicators and …