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Efflcient incremental decision tree generation for embedded applications
International Conference on Computational Intelligence and Security, 2004 Swere, Mulvaney, Sillitoe
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Incremental tuning of fuzzy decision trees
The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012Handling stream data or temporal data is a difficult task and brings out a lot of problems to classical learning algorithms as the decision tree construction algorithms. In that context, incremental algorithms have been proposed but they often lie on the frequent reconstruction of the decision tree when this one provides a high number of misclassified ...
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Incrementally optimized decision tree for noisy big data
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, 2012How to extract meaningful information from big data has been a popular open problem. Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference.
Hang Yang, Simon Fong
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Incremental and Interpretable Learning Analytics Through Fuzzy Hoeffding Decision Trees
2023Abstract Artificial Intelligence-based methods have been thoroughly applied in various fields over the years and theeducational scenario is not an exception. However, the usage of the so-called explainable ArtificialIntelligence, even if desirable, is still limited, especially whenever we consider educational datasets.Moreover, the time dimension is ...
Gabriella Casalino +3 more
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Efflcient incremental decision tree generation for embedded applications
IEEE Conference on Cybernetics and Intelligent Systems, 2004., 2005This paper describes a frequency table-based decision tree algorithm for embedded applications. The table contains a compact statistical representation of the training set feature vectors and can be used in conjunction with a variety of learning methods.
Erick Swere +2 more
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INCREMENTAL LEARNING DECISION TREE ALGORITHM FOR KNOWLEDGE DISCOVERY
PONTE International Scientific Researchs Journal, 2016A prominent learning discovery procedure is Data Mining. Decision trees are of the basic and intense decision making models in data mining. A single constraint in decision trees is the unpredictability and error rate. Motivated by human learning techniques, we suggest a decision tree structure which impersonates human adapting by performing consistent ...
Mohammed Ali Hussain, Mohammed Moulana
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Fuzzy Hoeffding Decision Trees for Incremental and Interpretable Predictions of Students' Outcomes
2022Pre-Print of the ...
Gabriella Casalino +3 more
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Incremental Induction of Belief Decision Trees in Averaging Approach
2014This paper extends the belief decision tree learning method to an incremental mode where the tree structure could change when new data come. This so-called incremental belief decision tree is a new classification method able to learn new instances incrementally, by updating and restructuring an existing belief decision tree.
Salsabil Trabelsi +2 more
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