Nonlinear regression via incremental decision trees [PDF]
Pattern Recognition, 2018 Abstract We study sequential nonlinear regression and introduce an online algorithm that elegantly mitigates, via an adaptively incremental hierarchical structure, convergence and undertraining issues of conventional nonlinear regression methods.
N. Denizcan Vanli +4 more
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Incremental Optimization Mechanism for Constructing a Decision Tree in Data Stream Mining [PDF]
Mathematical Problems in Engineering, 2013 Imperfect data stream leads to tree size explosion and detrimental accuracy problems. Overfitting problem and the imbalanced class distribution reduce the performance of the original decision-tree algorithm for stream mining. In this paper, we propose an incremental optimization mechanism to solve these problems.
Hang Yang, Simon Fong
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A configurable board-level adaptive incremental diagnosis technique based on decision trees [PDF]
2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS), 2015 Functional diagnosis for complex electronic boards is a time-consuming task that requires big expertise to the diagnosis engineers. In this paper we propose a new engine for board-level adaptive incremental functional diagnosis based on decision trees. The engine incrementally selects the tests that have to be executed and based on the test outcomes it
Cristiana Bolchini, Luca Cassano
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Costs and cost-effectiveness of integrated screening for non-communicable diseases in TB contacts [PDF]
IJTLD OpenBACKGROUND: Integrating non-communicable disease (NCD) screening into TB household contact investigations may identify undiagnosed NCDs and reduce the burden of both conditions.
Y. Hamada +9 more
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An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams [PDF]
, 2007 One of most important algorithms for mining data streams is VFDT. It uses Hoeffding inequality to achieve a probabilistic bound on the accuracy of the tree constructed. Gama et al. have extended VFDT in two directions. Their system VFDTc can deal with continuous data and use more powerful classification techniques at tree leaves.
Tao Wang +3 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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Tenecteplase for ischemic stroke at 4.5 to 24 hours without thrombectomy: a cost-utility analysis from the perspective of Chinese healthcare system [PDF]
Frontiers in NeurologyBackgroundTenecteplase improves functional outcomes in acute ischemic stroke (AIS) patients treated 4.5 to 24 h after symptom onset who do not undergo thrombectomy. However, its cost-utility remains unexamined.MethodsA hybrid model combining a short-term
Maolin Chen +5 more
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Cost-Effectiveness Analysis of a Latent Tuberculosis Screening Program Among Healthcare Personnel [PDF]
Inquiry: The Journal of Health Care Organization, Provision, and FinancingScreening high-risk groups for Latent Tuberculosis Infection (LTBI) is crucial for TB elimination, as the large global reservoir of Mycobacterium tuberculosis bacilli poses a significant challenge to TB control globally.
Niludi Ranwanee Yasaratna MD +1 more
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Decision Tree Incremental Learning Algorithm Oriented Intelligence Data [PDF]
International Journal of Performability Engineering, 2018 Hongbin Wang
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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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