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Efficient Decision Trees for Tensor Regressions
Journal of Computational And Graphical StatisticsWe proposed the tensor-input tree (TT) method for scalar-on-tensor and tensor-on-tensor regression problems. We first address scalar-on-tensor problem by proposing scalar-output regression tree models whose input variable are tensors (i.e., multi-way ...
Hengrui Luo, Akira Horiguchi, Li Ma
semanticscholar +1 more source
In Search of Trees: Decision-Tree Policy Synthesis for Black-Box Systems via Search
AAAI Conference on Artificial IntelligenceDecision trees, owing to their interpretability, are attractive as control policies for (dynamical) systems. Unfortunately, constructing, or synthesising, such policies is a challenging task. Previous approaches do so by imitating a neural-network policy,
Emir Demirovi'c +2 more
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Proceedings of the 6th International Conference on Information Technology: IoT and Smart City, 2018
In theory of computation, a deterministic finite automaton (DFA) is a finite state machine that accepts/rejects finite strings of symbols and only produces a unique computation. This study aims to convert the extracted decision tree rules sets from decision tree algorithm and the learning path sequence of the learning management system.
Ace C. Lagman +3 more
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In theory of computation, a deterministic finite automaton (DFA) is a finite state machine that accepts/rejects finite strings of symbols and only produces a unique computation. This study aims to convert the extracted decision tree rules sets from decision tree algorithm and the learning path sequence of the learning management system.
Ace C. Lagman +3 more
openaire +1 more source
Soft regression trees: a model variant and a decomposition training algorithm
European Journal of Operational ResearchDecision trees are widely used for classification and regression tasks in a variety of application fields due to their interpretability and good accuracy.
Antonio Consolo +2 more
semanticscholar +1 more source
2015 IEEE Symposium Series on Computational Intelligence, 2015
While collecting data from network traffic, one can create classifiers that recognize threats, anomalies, or other events. The set of labelled Net Flow records collecting traffic statistics is a very useful source of decision rules that classify the records. These rules can be created automatically using machine learning techniques.
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While collecting data from network traffic, one can create classifiers that recognize threats, anomalies, or other events. The set of labelled Net Flow records collecting traffic statistics is a very useful source of decision rules that classify the records. These rules can be created automatically using machine learning techniques.
openaire +1 more source
Counting the Number of Perfect Matchings, and Generalized Decision Trees
Problems of Information Transmission, 2021Mikhail N. Vyalyi
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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