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Maximum Exploratory Equivalence in Trees

Luka Fürst, Uroš Čibej, Jurij Mihelič
2015 Proceedings of the 2015 Federated Conference on Computer Science and Information Systems  
In the paper, we define the maximum exploratory equivalence problem. We show that the defined problem is at least as hard the graph isomorphism problem.  ...  Furthermore, we show that for trees, a maximum exploratory equivalent partition leads to a globally optimal set of subgraph isomorphism constraints, whereas this is not necessarily the case for general  ...  {h(1) < h LUKA FÜRST ET AL.: MAXIMUM EXPLORATORY EQUIVALENCE IN TREES  ... 
doi:10.15439/2015f329 dblp:conf/fedcsis/FurstCM15 fatcat:ywpfkv6fmbgjzbe4svw6ajsdzu

A Symmetry-Breaking Node Equivalence for Pruning the Search Space in Backtracking Algorithms

Uroš Čibej, Luka Fürst, Jurij Mihelič
2019 Symmetry  
We first present a framework for various backtracking search algorithms, in which the equivalence is used to prune the search tree.  ...  In particular, we show that the verifier lies between P and NP -complete problems.  ...  Abbreviations The following abbreviations are used in this manuscript:  ... 
doi:10.3390/sym11101300 fatcat:t6ylgwj7jraydo5uixu27ddfua

Effects of Fire Severity and Woody Debris on Tree Regeneration for Exploratory Well Pads in Jack Pine (Pinus banksiana) Forests

Angelo T. Filicetti, Ryan A. LaPointe, Scott E. Nielsen
2021 Forests  
The height of regenerating trees on exploratory well pads decreased with fire severity (0.56 cm per 1% increase in fire severity) and was non-linearly related to coarse woody debris (peaking at 286 cm  ...  In this study, we compared the effects of wildfire and local variation in the amount of residual woody debris on natural regeneration in jack pine on exploratory well pads in Alberta's boreal forest.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  ... 
doi:10.3390/f12101330 fatcat:fazwvi62ijfa7lhpj33srwv6pi

The dynamics of grazed woodlands in southwest Queensland, Australia, and their effect on greenhouse gas emissions

J.L. Moore, S.M. Howden, G.M. McKeon, J.O. Carter, J.C. Scanlan
2001 Environment International  
An exploratory study was completed to investigate the likely impact of changes in burning practices and stock management on emissions.  ...  Effective management for sheep production results in the system acting as a net source ( $ 60 -200 kg CO 2 equivalents/ha/year).  ...  maximum limit.  ... 
doi:10.1016/s0160-4120(01)00075-7 pmid:11697662 fatcat:6zhswt55h5ajfi4jszpu3xv25m

Structural equation model trees

Andreas M. Brandmaier, Timo von Oertzen, John J. McArdle, Ulman Lindenberger
2013 Psychological methods  
SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in  ...  SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration  ...  Put differently, in the maximum likelihood setting, a SEM Tree has the maximum likelihood of having observed the data set given that particular tree structure.  ... 
doi:10.1037/a0030001 pmid:22984789 pmcid:PMC4386908 fatcat:jfunmpi7vfaxjnb2ske223bs34

The geometric mean length, a new statistic to describe the distribution of character steps on a tree

Philippe Grandcolas, Tony Robillard, Cyrille D'Haese, Laure Desutter-Grandcolas, Eric Guilbert, Jerome Murienne
2004 Cladistics  
It can be scaled according to its theoretical maximum value, thus indicating a relative GML that allows a comparison of the evenness of character steps between different tree topologies.  ...  It is the geometric mean of the number of steps on each branch of the tree, varying between a maximum value when all branch lengths are equal, and a minimum value when all branches but one have only one  ...  Laet and three anonymous referees who have commented on a first version of this manuscript, and to those who commented on a talk given during the annual meeting of the Willi Hennig Society, Hennig XXII, in  ... 
doi:10.1111/j.1096-0031.2004.00017.x pmid:34892937 fatcat:u4pmwwynnngwvfn4d7pcqmi6jy

Coronary Illness Prediction Using Random Forest Classifier [chapter]

Rekha G, Shanthini B, Ranjith Kumar V
2021 Advances in Parallel Computing  
Here, we will use the various machine learning algorithms such as Support Vector Machine, Random Forest, KNN, Naive Bayes, Decision Tree and LR.  ...  Large datasets, which are not available in medical and clinical research, are required in order to apply deep learning techniques. Surrogate data is generated from Cleveland dataset.  ...  Decision Tree Classifier scores This graph shows the line graph from which we observed that the maximum accuracy is 81.97%.  ... 
doi:10.3233/apc210285 fatcat:7rdjxmwl7rb77fr5ogvi4jy44i

An optimal graph theoretic approach to data clustering: theory and its application to image segmentation

Z. Wu, R. Leahy
1993 IEEE Transactions on Pattern Analysis and Machine Intelligence  
This algorithm results in an optimal solution equivalent to that obtained by partitioning the complete equivalent tree and is able to handle very large graphs with several hundred thousand vertices.  ...  The segmentation is achieved by effectively searching for closed contours of edge elements (equivalent to minimum cuts in G), which consist mostly of strong edges, while rejecting contours containing isolated  ...  From Theorem 3, the equivalent tree 7' has arcs with capacity equal to the maximum flow between the vertices.  ... 
doi:10.1109/34.244673 fatcat:eisqkbw7vbfmhc6wje326zlsga

Batched Lazy Decision Trees [article]

Mathieu Guillame-Bert, Artur Dubrawski
2016 arXiv   pre-print
A set of experiments demonstrate that the proposed algorithm can outperform both the conventional and lazy decision tree algorithms in terms of computation time as well as memory consumption, without compromising  ...  We introduce a batched lazy algorithm for supervised classification using decision trees.  ...  In practice, unless the number of unlabeled observations is small, lazy decision trees can be slower in prediction mode than the equivalent eager decision trees.  ... 
arXiv:1603.02578v1 fatcat:sygkxwsibndm3fa7msqqnzs6ou

Fault Detection Techniques Prioritization using Bee Colony Optimization and then Comparison with Ant Colony Optimization

Mandeep KaurBedi, Sheena Singh
2013 International Journal of Computer Applications  
Research in software testing has experienced a significant growth in recent years. One topic of special interest is fault detection techniques to reduce human interference and detect maximum faults.  ...  Bee Colony Optimization based upon natural phenomena algorithm is used in it to find out the best results.  ...  Equivalence Partitioning (EP): Equivalence Partitioning is a technique in which divide the software or system into groups or into smaller parts which are also behave in a same manner.  ... 
doi:10.5120/12062-8077 fatcat:nyczo3ytwja5xlho4zwroqzd6q

Boldness behavior and stress physiology in a novel urban environment suggest rapid correlated evolutionary adaptation

Jonathan W. Atwell, Gonçalo C. Cardoso, Danielle J. Whittaker, Samuel Campbell-Nelson, Kyle W. Robertson, Ellen D. Ketterson
2012 Behavioral Ecology  
We found persistent population differences for both reduced CORT responses and bolder exploratory behavior in birds from the colonist population, as well as significant negative covariation between maximum  ...  We also measured CORT and exploratory behavior in birds raised from early life in a captive common garden study.  ...  Figure 4 Individual variation for maximum CORT and exploratory behavior from the common garden study.  ... 
doi:10.1093/beheco/ars059 pmid:22936840 pmcid:PMC3431113 fatcat:fkuzxvvehfgbxcnfkpcsctxr4i

Decomposition of quantitative Gaifman graphs as a data analysis tool

José Luis Balcázar, Marie Ely Piceno, Laura Rodríguez-Navas
2019 Zenodo  
We argue the usefulness of Gaifman graphs of rst-order relational structures as an exploratory data analysis tool.  ...  Since the maximum multiplicity of the edges in the Gaifman graph of Zoo is 81, we obtain four equivalence classes, but we do not see all of them: this is due simply to our visualization limits.  ...  Continuing Example 1, the tree decomposition of the 2-structure in Figure 1 (center) is displayed in Figure 2 (left).  ... 
doi:10.5281/zenodo.2581308 fatcat:cguhl3toerdazawzrexjcp6hlq

Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques

Laboni Akter, Ferdib-Al-Islam, Md. Milon Islam, Mabrook S. Al-Rakhami, Md. Rezwanul Haque
2021 SN Computer Science  
Cervical cancer growth is the fourth maximum of regular diseases in females.  ...  In this research, we have proposed three machine learning models such as Decision Tree, Random Forest, and XGBoost to predict cervical cancer from behavior and its variables and we got significantly improved  ...  Then again, when the estimation of X is the highest in the column, the numerator is equivalent to the denominator and in this way, the estimation of X′ is 1.  ... 
doi:10.1007/s42979-021-00551-6 fatcat:sm3qgs5xirde3h7gnni54h3ssy

Hunting multiple bumps in graphs

Yahui Sun, Jun Luo, Theodoros Lappas, Xiaokui Xiao, Bin Cui
2020 Proceedings of the VLDB Endowment  
We further prove that PCSFP is NP-hard even in trees. Then, we propose a fast approximation algorithm for solving PCSFP in trees.  ...  Recently, it has been explored for graph datasets for the first time, and a single bump is hunted in an unweighted graph in this exploration.  ...  subtrees in some trees that may have larger net-weights than the maximum-net-weight subtrees in some other trees.  ... 
doi:10.14778/3377369.3377375 fatcat:fney4ed7uzh6fa3xq3lm6u7fsi

metboost: Exploratory regression analysis with hierarchically clustered data [article]

Patrick J. Miller, Daniel B. McArtor, Gitta H. Lubke
2017 arXiv   pre-print
A machine learning method called boosted decision trees (Friedman, 2001) is a good approach for exploratory regression analysis in real data sets because it can detect predictors with nonlinear and interaction  ...  As data collections become larger, exploratory regression analysis becomes more important but more challenging.  ...  It is important to tune the maximum depth of the trees or the minimum number of observations in each node because it governs the complexity of the interactions that can be approximated by each tree.  ... 
arXiv:1702.03994v1 fatcat:nucicl7tkbdajhvvn2gt45ciiq
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