Results 41 to 50 of about 1,169,808 (377)
Multiple Instance Learning with Trainable Soft Decision Tree Ensembles
Algorithms, 2023 A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed.
Andrei Konstantinov +2 more
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Top-Down Induction of Decision Trees: Rigorous Guarantees and Inherent Limitations [PDF]
, 2019 Consider the following heuristic for building a decision tree for a function $f : \{0,1\}^n \to \{\pm 1\}$. Place the most influential variable $x_i$ of $f$ at the root, and recurse on the subfunctions $f_{x_i=0}$ and $f_{x_i=1}$ on the left and right ...
Blanc, Guy, Lange, Jane, Tan, Li-Yang
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METHOD OF BUILDING THE SEMANTIC NETWORK OF DISTRIBUTED SEARCH IN E-LEARNING
Сучасний стан наукових досліджень та технологій в промисловості, 2017 The subject matter of the article is semantic networks of distributed search in e-learning. The goal is to synthesize a decision tree and a stratified semantic network that allows network intelligent agents in the e-learning to construct inference ...
Nina Kuchuk +2 more
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Comprehensive decision tree models in bioinformatics.
PLoS ONE, 2012 PurposeClassification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of
Gregor Stiglic +3 more
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Frontiers in Oncology, 2023 BackgroundTo investigate the contribution of machine learning decision tree models applied to perfusion and spectroscopy MRI for multiclass classification of lymphomas, glioblastomas, and metastases, and then to bring out the underlying key ...
Rodolphe Vallée +14 more
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A Monte Carlo Tree Search Approach to Learning Decision Trees [PDF]
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018 Comunicació presentada a: 17th IEEE International Conference on Machine Learning and Applications (ICMLA) celebrada del 17 al 20 de 2018 a Orlando, Estats Units.
Nunes, Cecilia +4 more
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Quality Diversity Evolutionary Learning of Decision Trees
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023 Addressing the need for explainable Machine Learning has emerged as one of the most important research directions in modern Artificial Intelligence (AI). While the current dominant paradigm in the field is based on black-box models, typically in the form of (deep) neural networks, these models lack direct interpretability for human users, i.e., their ...
Andrea Ferigo +2 more
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Inducing safer oblique trees without costs [PDF]
, 2005 Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly ...
Althoff K. +27 more
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Applied Medical Informatics, 2023 Stroke is an acute neurologic disorder of blood vessels in brain due to blockage of blood flow to the brain resulting in less oxygen. Stroke remains one of the leading causes of death worldwide.
Helmi Saifullah MANSUR +2 more
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Interpretable land cover classification with modal decision trees
European Journal of Remote Sensing, 2023 Land cover classification (LCC) refers to the task of classifying each pixel in satellite/aerial imagery by predicting a label carrying information about its nature.
G. Pagliarini, G. Sciavicco
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