An Incremental Decision Tree for Mining Multilabel Data [PDF]
Applied Artificial Intelligence, 2015 Peipei Li +3 more
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Automated Screening for Three Inborn Metabolic Disorders: A Pilot Study [PDF]
Online Journal of Health & Allied Sciences, 2006 Background: Inborn metabolic disorders (IMDs) form a large group of rare, but often serious, metabolic disorders. Aims: Our objective was to construct a decision tree, based on classification algorithm for the data on three metabolic disorders, enabling ...
Kavitha S, Sarbadhikari SN, Ananth N Rao
doaj +2 more sources
A review: The effects of imperfect data on incremental decision tree
2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 2017 Zhiqiang Lin +4 more
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Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner [PDF]
European Conference on Machine Learning, 2001 Kurt Driessens +2 more
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Cost-effectiveness assessment of liquid biopsy for early detection of lung cancer in Brazil. [PDF]
PLoS ONEIntroductionLung cancer has a low survival rate due to late diagnosis, with most cases detected at advanced stages. Liquid biopsy, a non-invasive alternative to tissue biopsy, has emerged as a potential screening tool for early lung cancer detection ...
Kátia Marie Senna +5 more
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Incremental decision tree based on order statistics
IEEE International Joint Conference on Neural Network, 2013 Christophe Salperwyck, Vincent Lemaire
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IMPLEMENTATION OF DYNAMIC AND FAST MINING ALGORITHMS ON INCREMENTAL DATASETS TO DISCOVER QUALITATIVE RULES [PDF]
Applied Computer Science, 2021 Association Rule Mining is an important field in knowledge mining that allows the rules of association needed for decision making. Frequent mining of objects presents a difficulty to huge datasets. As the dataset gets bigger and more time and burden to
Pannangi NARESH, R. SUGUNA
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Dynamic Weights Based Risk Rule Generation Algorithm for Incremental Data of Customs Declarations
Information, 2023 Aimed at shortcomings, such as fewer risk rules for assisting decision-making in customs entry inspection scenarios and relying on expert experience generation, a dynamic weight assignment method based on the attributes of customs declaration data and an
Ding Han +3 more
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Parallel Incremental Mining of Regular-Frequent Patterns from WSNs Big Data [PDF]
Journal of Artificial Intelligence and Data Mining, 2023 Efficient regular-frequent pattern mining from sensors-produced data has become a challenge. The large volume of data leads to prolonged runtime, thus delaying vital predictions and decision makings which need an immediate response.
Sadegh Rahmani-Boldaji +2 more
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Machine Learning Methods with Decision Forests for Parkinson’s Detection
Applied Sciences, 2021 Biomedical engineers prefer decision forests over traditional decision trees to design state-of-the-art Parkinson’s Detection Systems (PDS) on massive acoustic signal data.
Moumita Pramanik +4 more
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