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Márcio P. Basgalupp, Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas, Duncan D. Ruiz
2009 Proceedings of the 2009 ACM symposium on Applied Computing - SAC '09  
Decision trees are widely disseminated as an effective solution for classification tasks.  ...  Decision tree induction algorithms have some limitations though, due to the typical strategy they implement: recursive top-down partitioning through a greedy split evaluation.  ...  Note that, to the best of our knowledge, a lexicographic approach has not yet been used for evolutionary decision tree induction.  ... 
doi:10.1145/1529282.1529521 dblp:conf/sac/BasgaluppBCFR09 fatcat:4pqtttv7vzgfdkedkaa2z3zacm

Evolutionary Algorithm for Decision Tree Induction [chapter]

Dariusz Jankowski, Konrad Jackowski
2014 Lecture Notes in Computer Science  
by the European Social Fund and the state budget of the Czech Republic.  ...  This work was supported by the statutory funds of the Department of Systems and Computer Networks, Faculty of Electronics, Wroclaw University of Technology dedicated for Young Scientists (grant no.  ...  or controlling parameters of trees [15] . 4 The EVO-Tree Algorithm EVO-Tree (EVOlutionary Algorithm for Decision Tree Induction) is a novel multiobjective evolutionary algorithm proposed to evolve  ... 
doi:10.1007/978-3-662-45237-0_4 fatcat:vsqqnkgrszg4tcw6fachj2vxq4

A Monte Carlo Tree Search Approach to Learning Decision Trees

Cecilia Nunes, Mathieu De Craene, Helene Langet, Oscar Camara, Anders Jonsson
2018 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)  
To bound the branching factor of MCTS, we limit the number of decisions at each level of the search tree, and introduce mechanisms to balance exploration, DT size and the statistical significance of the  ...  Decision trees (DTs) are a widely used prediction tool, owing to their interpretability.  ...  ACKNOWLEDGMENTS This work was supported by the European Union Horizon 2020 research and innovation programme (grant 642676 -Cardiofunxion), and by the Spanish Ministry of Economy and Competitiveness (grant  ... 
doi:10.1109/icmla.2018.00070 dblp:conf/icmla/NunesCLCJ18 fatcat:z2rd6vsf2fairdlbfxk4ojbbcy

Hyper-heuristic decision tree induction

Alan Vella, David Corne, Chris Murphy
2009 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC)  
The result of hyper-heuristic search in this case is a new decision tree induction algorithm.  ...  We show that hyperheuristic search over a space of decision tree induction rules is able to find decision tree induction algorithms that outperform many different version of ID3 on unseen test sets.  ...  ACKNOWLEDGEMENT We thank Motorola Ltd for sponsorship of this work.  ... 
doi:10.1109/nabic.2009.5393568 dblp:conf/nabic/VellaCM09 fatcat:25o37c2xc5as7ir5q6ny5tubte

Mixed Decision Trees: An Evolutionary Approach [chapter]

Marek Krȩtowski, Marek Grześ
2006 Lecture Notes in Computer Science  
In the paper, a new evolutionary algorithm (EA) for mixed tree learning is proposed.  ...  In non-terminal nodes of a mixed decision tree different types of tests can be placed, ranging from a typical univariate inequality test up to a multivariate test based on a splitting hyperplane.  ...  This work was supported by the grant W/WI/5/05 from Bia lystok Technical University.  ... 
doi:10.1007/11823728_25 fatcat:g4bksdgkwnghrgcx7iijqie5gm

Evolutionary model tree induction

Rodrigo C. Barros, Márcio P. Basgalupp, Duncan D. Ruiz, André C. P. L. F. de Carvalho, Alex A. Freitas
2010 Proceedings of the 2010 ACM Symposium on Applied Computing - SAC '10  
Evolutionary Model Tree Induction Model trees are a particular case of decision trees employed to solve regression problems, where the variable to be predicted is continuous.  ...  In this work, we propose the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to global optimal solutions.  ...  states of the system and also limits what the system can learn.  ... 
doi:10.1145/1774088.1774327 dblp:conf/sac/BarrosBRCF10 fatcat:jygkpgrfujhvdhpzigbez3m6xq

A Survey of Evolutionary Algorithms for Decision-Tree Induction

Rodrigo Coelho Barros, Márcio Porto Basgalupp, André C. P. L. F. de Carvalho, Alex A. Freitas
2012 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
This paper presents a survey of evolutionary algorithms designed for decision tree induction.  ...  Finally, a number of references is provided that describe applications of evolutionary algorithms for decision tree induction in different domains.  ...  ACKNOWLEDGMENT The authors would like to thank Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de  ... 
doi:10.1109/tsmcc.2011.2157494 fatcat:wo3ak7qiwrcz5fosspwjgstjfi

Evolutionary Learning of Linear Trees with Embedded Feature Selection [chapter]

Marek Krętowski, Marek Grześ
2006 Lecture Notes in Computer Science  
In the paper a new evolutionary algorithm for global induction of linear trees is presented.  ...  The learning process consists of searching for both a decision tree structure and hyper-plane weights in all nonterminal nodes.  ...  This work was supported by the grant W/WI/5/05 from Bia lystok Technical University.  ... 
doi:10.1007/11785231_43 fatcat:z25wavtbofguxaftprp2mmvmtq

Tree Based Advanced Relative Expression Analysis [chapter]

Marcin Czajkowski, Krzysztof Jurczuk, Marek Kretowski
2020 Lecture Notes in Computer Science  
The main contribution is a decision tree with splitting nodes that consider relative fraction comparisons between multiple gene pairs.  ...  The basic idea of RXA is to focus on simple ordering relationships between the expression of small sets of genes rather than their raw values.  ...  This project was funded by the Polish National Science Center and allocated on the basis of decision 2019/33/B/ST6/02386 (first author).  ... 
doi:10.1007/978-3-030-50420-5_37 fatcat:ygf7xp4gyjftbk64eevltopwf4

Language trees ≠ gene trees

James Steele, Anne Kandler
2010 Theory in biosciences  
Such interpretations are supported when the distributions of shared and unshared traits (for example, in terms of etymological roots for elements of basic vocabulary) are analysed using tree-building techniques  ...  In this article, we question the demographic assumption which is sometimes made when a tree-building approach has been taken to a set of cultures or languages, namely that the resulting tree is also representative  ...  Acknowledgements We thank Nathalie Gontier and co-organizers of the Evolution today and tomorrow conference in Lisbon for the opportunity to participate in this symposium.  ... 
doi:10.1007/s12064-010-0096-6 pmid:20532998 fatcat:ax6bjrc7afdavaty2xrwmgcr4i

Global Induction of Oblique Model Trees: An Evolutionary Approach [chapter]

Marcin Czajkowski, Marek Kretowski
2013 Lecture Notes in Computer Science  
In this paper we propose a new evolutionary algorithm for global induction of oblique model trees that associates leaves with multiple linear regression models.  ...  The general structure of proposed solution follows a typical framework of evolutionary algorithms with an unstructured population and a generational selection.  ...  This work was supported by the grant S/WI/2/13 from Bialystok University of Technology.  ... 
doi:10.1007/978-3-642-38610-7_1 fatcat:q2xussd3snhl7kw6zzevhbilyi

An Evolutionary Algorithm for Global Induction of Regression Trees [chapter]

Marek Krȩtowski, Marcin Czajkowski
2010 Lecture Notes in Computer Science  
In the paper a new evolutionary algorithm for induction of univariate regression trees is proposed.  ...  The population of initial trees is created with diverse topdown methods on randomly chosen sub-samples of the training data.  ...  This work was supported by the grant W/WI/5/10 from Bialystok University of Technology.  ... 
doi:10.1007/978-3-642-13232-2_19 fatcat:u5hgaafiknfg3ezn354zlsq5ha

Method trees

Ingo Mierswa, Katharina Morik
2005 Proceedings of the 2005 workshops on Genetic and evolutionary computation - GECCO '05  
The practical use of the methods is shown by two types of experiments in the domain of music data classification: classification of genres and classification according to user preferences.  ...  Our approach to evolve representations from series data requires a balance between the completeness of the methods on one side and the tractability of searching for appropriate methods on the other side  ...  The use of features can also be inspected by restricting a top-down induction of decision trees to a few levels.  ... 
doi:10.1145/1102256.1102322 dblp:conf/gecco/MierswaM05 fatcat:4qa5bf32kze6vl326rmjcp37vm

Multi-GPU approach to global induction of classification trees for large-scale data mining

Krzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski
2021 Applied intelligence (Boston)  
AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers.  ...  When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.  ...  Evolutionary induction of decision trees In the beginning, basic information about decision trees, methods in their induction and evolutionary algorithms are presented.  ... 
doi:10.1007/s10489-020-01952-5 fatcat:nv2pudcn5jafldo2jodrjdkode

Clus-DTI: improving decision-tree classification with a clustering-based decision-tree induction algorithm

Rodrigo C. Barros, Márcio P. Basgalupp, André C. P. L. F. de Carvalho, Marcos G. Quiles
2012 Journal of the Brazilian Computer Society  
Most decision-tree induction algorithms rely on a suboptimal greedy top-down recursive strategy for growing the tree.  ...  Our intention is to investigate how clustering data as a part of the induction process affects the accuracy and complexity of the generated models.  ...  The main disadvantages of evolutionary induction of decision trees are related to time and space constraints. EAs are a solid but computational expensive heuristic.  ... 
doi:10.1007/s13173-012-0075-5 fatcat:47erso2hgvdxrhdpnz6nbpto4e
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