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An Improved Algorithm for Incremental Induction of Decision Trees
, 1994 This paper presents an algorithm for incremental induction of decision trees that is able to handle both numeric and symbolic variables. In order to handle numeric variables, a new tree revision operator called 'slewing' is introduced. Finally, a non-incremental method is given for finding a decision tree based on a direct metric of a candidate tree.
Paul E. Utgoff
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Adaptive Board-Level Functional Fault Diagnosis Using Incremental Decision Trees
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2016Board-level functional fault diagnosis is needed for high-volume production to improve product yield. However, to ensure diagnosis accuracy and effective board repair, a large number of syndromes must be used. Therefore, the diagnosis cost can be prohibitively high due to the increase in diagnosis time and the complexity of test execution and analysis.
Zhaobo Zhang +3 more
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STABLE DECISION TREES: USING LOCAL ANARCHY FOR EFFICIENT INCREMENTAL LEARNING
International Journal on Artificial Intelligence Tools, 2000 This work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree very often and oscillations between similar concepts decrease learning speed. We introduce a heuristic and an algorithm with theoretical and experimental backing to tackle this problem.
Dimitris Kalles, Athanasios Papagelis
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2008 Fourth International Conference on Networked Computing and Advanced Information Management, 2008
This paper proposed a diagnostic supporting tool - i+DiaKAW (intelligent and interactive knowledge acquisition workbench), which automatically extracts useful knowledge from massive medical data by applying various data mining techniques for supporting real medical diagnosis.
Yiping Li, Fai Wong, Sam Chao
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This paper proposed a diagnostic supporting tool - i+DiaKAW (intelligent and interactive knowledge acquisition workbench), which automatically extracts useful knowledge from massive medical data by applying various data mining techniques for supporting real medical diagnosis.
Yiping Li, Fai Wong, Sam Chao
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A New Incremental Algorithm for Induction of Multivariate Decision Trees for Large Datasets
, 2008 Several algorithms for induction of decision trees have been developed to solve problems with large datasets, however some of them have spatial and/or runtime problems using the whole training sample for building the tree and others do not take into account the whole training set.
Anilú Franco-Árcega +3 more
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Lightweight Privacy-Preserving Federated Incremental Decision Trees
IEEE Transactions on Services Computing, 2023Tree-based models are wildly adopted in various real-world scenarios. Recently, there is a growing interest in vertical federated tree-based model learning to build tree-based models by exploiting data from multiple organizations without violating data ...
Zhaoyang Han +3 more
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Energy Technology, 2023
Accurately battery state of health (SOH) estimation in electric vehicles (EVs) is crucial for optimal performance and safety. This article presents an in‐depth investigation into the utilization of an optimized decision tree (DT) model for precise SOH ...
Xingzi Qiang +3 more
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Accurately battery state of health (SOH) estimation in electric vehicles (EVs) is crucial for optimal performance and safety. This article presents an in‐depth investigation into the utilization of an optimized decision tree (DT) model for precise SOH ...
Xingzi Qiang +3 more
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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006 Erick Swere +2 more
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Regularized and incremental decision trees for data streams
Annals of Telecommunications, 2020Decision trees are a widely used family of methods for learning predictive models from both batch and streaming data. Despite depicting positive results in a multitude of applications, incremental decision trees continuously grow in terms of nodes as new data becomes available, i.e., they eventually split on all features available, and also multiple ...
Jean Paul Barddal, Fabrício Enembreck
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