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Relevant bibliographies by topics / Partition tree

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Academic literature on the topic 'Partition tree'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Partition tree"

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Mu, Yashuang, Lidong Wang, and Xiaodong Liu. "Dynamic programming based fuzzy partition in fuzzy decision tree induction." Journal of Intelligent & Fuzzy Systems 39, no. 5 (November 19, 2020): 6757–72. http://dx.doi.org/10.3233/jifs-191497.

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Fuzzy decision trees are one of the most popular extensions of decision trees for symbolic knowledge acquisition by fuzzy representation. Among the majority of fuzzy decision trees learning methods, the number of fuzzy partitions is given in advance, that is, there are the same amount of fuzzy items utilized in each condition attribute. In this study, a dynamic programming-based partition criterion for fuzzy items is designed in the framework of fuzzy decision tree induction. The proposed criterion applies an improved dynamic programming algorithm used in scheduling problems to establish an optimal number of fuzzy items for each condition attribute. Then, based on these fuzzy partitions, a fuzzy decision tree is constructed in a top-down recursive way. A comparative analysis using several traditional decision trees verify the feasibility of the proposed dynamic programming based fuzzy partition criterion. Furthermore, under the same framework of fuzzy decision trees, the proposed fuzzy partition solution can obtain a higher classification accuracy than some cases with the same amount of fuzzy items.

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ARKIN, ESTHER M., DELIA GARIJO, ALBERTO MÁRQUEZ, JOSEPH S. B. MITCHELL, and CARLOS SEARA. "SEPARABILITY OF POINT SETS BY k-LEVEL LINEAR CLASSIFICATION TREES." International Journal of Computational Geometry & Applications 22, no. 02 (April 2012): 143–65. http://dx.doi.org/10.1142/s0218195912500021.

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Let R and B be sets of red and blue points in the plane in general position. We study the problem of computing a k-level binary space partition (BSP) tree to classify/separate R and B, such that the tree defines a linear decision at each internal node and each leaf of the tree corresponds to a (convex) cell of the partition that contains only red or only blue points. Specifically, we show that a 2-level tree can be computed, if one exists, in time O(n2). We show that a minimum-level (3 ≤ k ≤ log n) tree can be computed in time nO( log n). In the special case of axis-parallel partitions, we show that 2-level and 3-level trees can be computed in time O(n), while a minimum-level tree can be computed in time O(n5).

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Wood, David R. "On tree-partition-width." European Journal of Combinatorics 30, no. 5 (July 2009): 1245–53. http://dx.doi.org/10.1016/j.ejc.2008.11.010.

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Proe, M. F., and P. Millard. "Effect of N supply upon the seasonal partitioning of N and P uptake in young Sitka spruce (Piceasitchensis)." Canadian Journal of Forest Research 25, no. 10 (October 1, 1995): 1704–9. http://dx.doi.org/10.1139/x95-184.

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Seasonal relationships between N supply, tree growth, and partitioning of both N and P have been studied in young trees using 15N and 32P isotopes. Three-year-old clonal cuttings of Sitka spruce (Piceasitchensis (Bong.) Carr.) were grown for 2 years in sand irrigated with a nutrient solution containing either 1.0 mol N•m−3 (low N) or 6.0 mol N•m−3 (high N). In the first year, trees received 2-week pulses of 15N and 32P to label current nutrient uptake during either a period of rapid spring growth or shortly after bud set in summer. In the second year, trees that had been preconditioned to a low-N supply received 3-week pulses of 15N at either the low rate of application or at the high rate to simulate a single application of N fertilizer. In spring of the first year, N treatment had no effect upon tree growth. Low-N trees increased the partition of 15N uptake to roots, but the partition of 32P was not affected by N supply and was similar to the partition of 15N in the high-N treatment. At the time of the later pulse, however, growth was affected by N supply and 32P partitioning to roots increased to match the partition of 15N in the low-N treatment. During the second year, the additional 15N given to Low-N trees to simulate fertilizer application was partitioned predominantly to current shoots and roots. Results are discussed in relation to the processes of internal cycling and the partition of nutrients taken up by larger trees.

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Katrenič, Peter, and Gabriel Semanišin. "On a tree-partition problem." Electronic Notes in Discrete Mathematics 28 (March 2007): 325–30. http://dx.doi.org/10.1016/j.endm.2007.01.046.

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HURTADO, FERRAN, GIUSEPPE LIOTTA, and DAVID R. WOOD. "PROXIMITY DRAWINGS OF HIGH-DEGREE TREES." International Journal of Computational Geometry & Applications 23, no. 03 (June 2013): 213–30. http://dx.doi.org/10.1142/s0218195913500088.

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A drawing of a given (abstract) tree that is a minimum spanning tree of the vertex set is considered aesthetically pleasing. However, such a drawing can only exist if the tree has maximum degree at most 6. What can be said for trees of higher degree? We approach this question by supposing that a partition or covering of the tree by subtrees of bounded degree is given. Then we show that if the partition or covering satisfies some natural properties, then there is a drawing of the entire tree such that each of the given subtrees is drawn as a minimum spanning tree of its vertex set.

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Gao, Jing. "Decision Tree Generation Algorithm without Pruning." Applied Mechanics and Materials 441 (December 2013): 731–37. http://dx.doi.org/10.4028/www.scientific.net/amm.441.731.

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On the generation of decision tree based on rough set model, for the sake of classification accuracy, existing algorithms usually partition examples too specific. And it is hard to avoid the negative impact caused by few special examples on decision tree. In order to obtain this priority in traditional decision tree algorithm based on rough set, the sample is partitioned much more meticulously. Inevitably, a few exceptional samples have negative effect on decision tree. And this leads that the generated decision tree seems too large to be understood. It also reduces the ability in classifying and predicting the coming data. To settle these problems, the restrained factor is introduced in this paper. For expanding nodes in generating decision tree algorithm, besides traditional terminating condition, an additional terminating condition is involved when the restrained factor of sample is higher than a given threshold, then the node will not be expanded any more. Thus, the problem of much more meticulous partition is avoided. Furthermore, the size of decision tree generated with restrained factor involved will not seem too large to be understood.

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Shan, Gui Jun. "Partition Real Data in Decision Tree Using Statistical Criterion." Applied Mechanics and Materials 380-384 (August 2013): 1469–72. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1469.

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Partition methods for real data play an extremely important role in decision tree algorithms in data mining and machine learning because the decision tree algorithms require that the values of attributes are discrete. In this paper, we propose a novel partition method for real data in decision tree using statistical criterion. This method constructs a statistical criterion to find accurate merging intervals. In addition, we present a heuristic partition algorithm to achieve a desired partition result with the aim to improve the performance of decision tree algorithms. Empirical experiments on UCI real data show that the new algorithm generates a better partition scheme that improves the classification accuracy of C4.5 decision tree than existing algorithms.

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Guttmann-Beck, Nili, and Refael Hassin. "Approximation algorithms for minimum tree partition." Discrete Applied Mathematics 87, no. 1-3 (October 1998): 117–37. http://dx.doi.org/10.1016/s0166-218x(98)00052-3.

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Tang, Jing, Yinghui Wang, Ningna Wang, Xiaojuan Ning, Ke Lyu, Liansheng Sui, and Zhenghao Shi. "Swaying Tree Simulation by Slicing Partition." Chinese Journal of Electronics 29, no. 5 (September 1, 2020): 826–32. http://dx.doi.org/10.1049/cje.2020.07.004.

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Dissertations / Theses on the topic "Partition tree"

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Ghanbari, Shirin. "Multi-Dimensional Binary Partition Tree for Content Retrieval." Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520046.

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Sundberg, Kenneth A. "Partition Based Phylogenetic Search." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2583.

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Evolutionary relationships are key to modern understanding of biological systems. Phylogenetic search is the means by which these relationships are inferred. Phylogenetic search is NP-Hard. As such it is necessary to employ heuristic methods. This work proposes new methods based on viewing the relationships between species as sets of partitions. These methods produce more parsimonious phylogenies than current methods.

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Sudirman. "Colour image coding indexing and retrieval using binary space partition tree." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275171.

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Agarwal, Khushbu. "A partition based approach to approximate tree mining a memory hierarchy perspective /." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1196284256.

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Agarwal, Khushbu. "A partition based approach to approximate tree mining : a memory hierarchy perspective." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1196284256.

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Tan, Kunlun. "On the Role of Partition Inequalities in Classical Algorithms for Steiner Problems in Graphs." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/1123.

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The Steiner tree problem is a classical, well-studied, $\mathcal{NP}$-hard optimization problem. Here we are given an undirected graph $G=(V,E)$, a subset $R$ of $V$ of terminals, and non-negative costs $c_e$ for all edges $e$ in $E$. A feasible Steiner tree for a given instance is a tree $T$ in $G$ that spans all terminals in $R$. The goal is to compute a feasible Steiner tree of smallest cost. In this thesis we will focus on approximation algorithms for this problem: a $c$-approximation algorithm is an algorithm that returns a tree of cost at most $c$ times that of an optimum solution for any given input instance.

In a series of papers throughout the last decade, the approximation guarantee $c$ for the Steiner tree problem has been improved to the currently best known value of 1. 55 (Robins, Zelikovsky). Robins' and Zelikovsky's algorithm as well as most of its predecessors are greedy algorithms.

Apart from algorithmic improvements, there also has been substantial work on obtaining tight linear-programming relaxations for the Steiner tree problem. Many undirected and directed formulations have been proposed in the course of the last 25 years; their use, however, is to this point mostly restricted to the field of exact optimization. There are few examples of algorithms for the Steiner tree problem that make use of these LP relaxations. The best known such algorithm for general graphs is a 2-approximation (for the more general Steiner forest problem) due to Agrawal, Klein and Ravi. Their analysis is tight as the LP-relaxation used in their work is known to be weak: it has an IP/LP gap of approximately 2.

Most recent efforts to obtain algorithms for the Steiner tree problem that are based on LP-relaxations has focused on directed relaxations. In this thesis we present an undirected relaxation and show that the algorithm of Robins and Zelikovsky returns a Steiner tree whose cost is at most 1. 55 times its optimum solution value. In fact, we show that this algorithm can be viewed as a primal-dual algorithm.

The Steiner forest problem is a generalization of the Steiner tree problem. In the problem, instead of only one set of terminals, we are given more than one terminal set. An feasible Steiner forest is a forest that connects all terminals in the same terminal set for each terminal set. The goal is to find a minimum cost feasible Steiner forest. In this thesis, a new set of facet defining inequalities for the polyhedra of the Steiner forest is introduced.

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Valero, Valbuena Silvia. "Arbre de partition binaire : un nouvel outil pour la représentation hiérarchique et l’analyse des images hyperspectrales." Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENT123/document.

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Résumé non communiqué par le doctorant
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. Therefore, under the title Hyperspectral image representation and Processing with Binary Partition Trees, this PhD thesis proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation:the Binary Partition Tree (BPT). This hierarchical region-based representation can be interpretedas a set of hierarchical regions stored in a tree structure. Hence, the Binary Partition Tree succeedsin presenting: (i) the decomposition of the image in terms of coherent regions and (ii) the inclusionrelations of the regions in the scene. Based on region-merging techniques, the construction of BPTis investigated in this work by studying hyperspectral region models and the associated similaritymetrics. As a matter of fact, the very high dimensionality and the complexity of the data require the definition of specific region models and similarity measures. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniqueson it. The application-dependent processing of BPT is generally implemented through aspecific pruning of the tree. Accordingly, some pruning techniques are proposed and discussed according to different applications. This Ph.D is focused in particular on segmentation, object detectionand classification of hyperspectral imagery. Experimental results on various hyperspectraldata sets demonstrate the interest and the good performances of the BPT representation

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Rattan, Amarpreet. "Parking Functions and Related Combinatorial Structures." Thesis, University of Waterloo, 2001. http://hdl.handle.net/10012/1028.

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The central topic of this thesis is parking functions. We give a survey of some of the current literature concerning parking functions and focus on their interaction with other combinatorial objects; namely noncrossing partitions, hyperplane arrangements and tree inversions. In the final chapter, we discuss generalizations of both parking functions and the above structures.

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Howell, Gareth. "Normalised distance function considered over the partition of the unit interval generated by the points of the Farey tree." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55096/.

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Law, Hiu-Fai. "Trees and graphs : congestion, polynomials and reconstruction." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:54190b51-cd9d-489e-a79e-82ecdf15b4c5.

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Spanning tree congestion was defined by Ostrovskii (2004) as a measure of how well a network can perform if only minimal connection can be maintained. We compute the parameter for several families of graphs. In particular, by partitioning a hypercube into pieces with almost optimal edge-boundaries, we give tight estimates of the parameter thereby disproving a conjecture of Hruska (2008). For a typical random graph, the parameter exhibits a zigzag behaviour reflecting the feature that it is not monotone in the number of edges. This motivates the study of the most congested graphs where we show that any graph is close to a graph with small congestion. Next, we enumerate independent sets. Using the independent set polynomial, we compute the extrema of averages in trees and graphs. Furthermore, we consider inverse problems among trees and resolve a conjecture of Wagner (2009). A result in a more general setting is also proved which answers a question of Alon, Haber and Krivelevich (2011). After briefly considering polynomial invariants of general graphs, we specialize into trees. Three levels of tree distinguishing power are exhibited. We show that polynomials which do not distinguish rooted trees define typically exponentially large equivalence classes. On the other hand, we prove that the rooted Ising polynomial distinguishes rooted trees and that the Negami polynomial determines the subtree polynomial, strengthening results of Bollobás and Riordan (2000) and Martin, Morin and Wagner (2008). The top level consists of the chromatic symmetric function and it is proved to be a complete invariant for caterpillars.

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Book chapters on the topic "Partition tree"

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Danda, Sravan, Aditya Challa, and B. S. Daya Sagar. "Binary Partition Tree." In Encyclopedia of Mathematical Geosciences, 1–2. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_54-1.

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Schweitzer, Marc Alexander. "Tree Partition of Unity Method." In Lecture Notes in Computational Science and Engineering, 97–126. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-59325-3_5.

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Deifel, Hans-Peter, Stefan Milius, Lutz Schröder, and Thorsten Wißmann. "Generic Partition Refinement and Weighted Tree Automata." In Lecture Notes in Computer Science, 280–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30942-8_18.

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Li, Zhen, Aili Han, and Feilin Han. "A Novel Attributes Partition Method for Decision Tree." In Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013, 435–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37502-6_52.

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Okubo, Masahiro, Tesshu Hanaka, and Hirotaka Ono. "Optimal Partition of a Tree with Social Distance." In WALCOM: Algorithms and Computation, 121–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-10564-8_10.

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Salembier, Philippe. "Study of Binary Partition Tree Pruning Techniques for Polarimetric SAR Images." In Lecture Notes in Computer Science, 51–62. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18720-4_5.

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Lin, Mugang, Wenjun Li, and Qilong Feng. "Parameterized Minimum Cost Partition of a Tree with Supply and Demand." In Frontiers in Algorithmics, 180–89. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19647-3_17.

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Blum, Christian, José A. Lozano, and Pedro Pinacho Davidson. "Iterative Probabilistic Tree Search for the Minimum Common String Partition Problem." In Hybrid Metaheuristics, 145–54. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07644-7_11.

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Leitner, Markus, Ivana Ljubić, Martin Luipersbeck, and Max Resch. "A Partition-Based Heuristic for the Steiner Tree Problem in Large Graphs." In Hybrid Metaheuristics, 56–70. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07644-7_5.

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You, Jie, Jianxin Wang, and Qilong Feng. "Parameterized Algorithms for Minimum Tree Cut/Paste Distance and Minimum Common Integer Partition." In Frontiers in Algorithmics, 99–111. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78455-7_8.

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Conference papers on the topic "Partition tree"

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Veness, J., M. White, M. Bowling, and A. Gyorgy. "Partition Tree Weighting." In 2013 Data Compression Conference (DCC). IEEE, 2013. http://dx.doi.org/10.1109/dcc.2013.40.

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Decrouez, Geoffrey, and Pierre-Olivier Amblard. "Crossing-tree partition functions." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362535.

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Drumetz, L., M. A. Veganzones, R. Marrero, G. Tochon, M. Dalla Mura, A. Plaza, and J. Chanussot. "Binary partition tree-based local spectral unmixing." In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2014. http://dx.doi.org/10.1109/whispers.2014.8077555.

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Huang, Hsin-Hsiung, Yu-Cheng Lin, Hui-Yu Huang, and Tsai-Ming Hsieh. "Partition-based Routing Tree Algorithm with Obstacles." In 2007 International Symposium on Integrated Circuits. IEEE, 2007. http://dx.doi.org/10.1109/isicir.2007.4441825.

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Zhang, Yunpeng, Zhengjun Zhai, Lu Zhang, Yifei Bao, Weidi Dai, and Fei Zuo. "Partition-Based Parallel Constructing-Density-Tree Clustering." In 2008 International Symposiums on Information Processing ISIP. IEEE, 2008. http://dx.doi.org/10.1109/isip.2008.121.

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Palou, Guillem, and Philippe Salembier. "Hierarchical Video Representation with Trajectory Binary Partition Tree." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.273.

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Valero, Silvia, Philippe Salembier, and Jocelyn Chanussot. "New hyperspectral data representation using binary partition tree." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5649780.

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Yu, Xingxing, Jinli Xie, and Haiqing Hu. "Rough set based attributes partition in decision tree." In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8243844.

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Wang, Liqiang, Xiaoran Cao, Benben Niu, Quanhe Yu, Jianhua Zheng, and Yun He. "Derived Tree Block Partition for AVS3 Intra Coding." In 2019 Picture Coding Symposium (PCS). IEEE, 2019. http://dx.doi.org/10.1109/pcs48520.2019.8954542.

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Shinkai, Kimiaki, Hajime Yamashitar, and Shuya Kanagawa. "Decision Analysis of Fuzzy Partition Tree Applying Fuzzy Theory." In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.236.

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