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Educational Data Mining Using Cluster Analysis Methods and Decision Trees based on Log Mining
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Educational Data Mining (EDM) often appears to be applied in big data processing in the education sector. One of the educational data that can be further processed with EDM is activity log data from an e-learning system used in teaching and learning ...
Safira Nuri Safitri +2 more
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The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm
Complexity, 2021 With the continuous development of “Internet + Education”, online learning has become a hot topic of concern. Decision tree is an important technique for solving classification problems from a set of random and unordered data sets.
Yongxian Yang
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Robust algorithm to learn rules for classification: A fault diagnosis case study [PDF]
FME Transactions, 2023 Machine learning algorithms are used for building classifier models. The rule-based decision tree classifiers are popular ones. However, the performance of the decision tree classifier varies with hyperparameter tuning.
Balaji Arun P., Sugumaran V.
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Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm
Discrete Dynamics in Nature and Society, 2022 With the research of machine learning technology and big data intelligent processing technology in engineering application becoming more and more mature, people gradually combine machine learning technology and big data intelligent processing technology.
Fen Yang
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Attribute Selection Based on Constraint Gain and Depth Optimal for a Decision Tree
Entropy, 2019 Uncertainty evaluation based on statistical probabilistic information entropy is a commonly used mechanism for a heuristic method construction of decision tree learning.
Huaining Sun, Xuegang Hu, Yuhong Zhang
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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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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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Decision Tree Learning for Uncertain Clinical Measurements [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2021 Clinical decision requires reasoning in the presence of imperfect data. DTs are a well-known decision support tool, owing to their interpretability, fundamental in safety-critical contexts such as medical diagnosis. However, learning DTs from uncertain data leads to poor generalization, and generating predictions for uncertain data hinders prediction ...
Cecilia Nunes +5 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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