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Journal articles on the topic 'Random k-SAT'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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1

Larsson, Joel, and Klas Markström. "Biased random k ‐SAT." Random Structures & Algorithms 59, no. 2 (February 16, 2021): 238–66. http://dx.doi.org/10.1002/rsa.20996.

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2

Coja-Oghlan, Amin, and Angelica Y. Pachon-Pinzon. "The Decimation Process in Random $k$-SAT." SIAM Journal on Discrete Mathematics 26, no. 4 (January 2012): 1471–509. http://dx.doi.org/10.1137/110842867.

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3

Coja-Oghlan, Amin. "A Better Algorithm for Random k-SAT." SIAM Journal on Computing 39, no. 7 (January 2010): 2823–64. http://dx.doi.org/10.1137/09076516x.

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4

COJA-OGHLAN, AMIN, ANDREAS GOERDT, and ANDRÉ LANKA. "Strong Refutation Heuristics for Random k-SAT." Combinatorics, Probability and Computing 16, no. 01 (August 14, 2006): 5. http://dx.doi.org/10.1017/s096354830600784x.

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5

Kravitz, David. "On an online random k-SAT model." Random Structures and Algorithms 32, no. 1 (2007): 115–24. http://dx.doi.org/10.1002/rsa.20200.

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6

Cai, S., C. Luo, and K. Su. "Scoring Functions Based on Second Level Score for k-SAT with Long Clauses." Journal of Artificial Intelligence Research 51 (October 22, 2014): 413–41. http://dx.doi.org/10.1613/jair.4480.

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It is widely acknowledged that stochastic local search (SLS) algorithms can efficiently find models for satisfiable instances of the satisfiability (SAT) problem, especially for random k-SAT instances. However, compared to random 3-SAT instances where SLS algorithms have shown great success, random k-SAT instances with long clauses remain very difficult. Recently, the notion of second level score, denoted as "score_2", was proposed for improving SLS algorithms on long-clause SAT instances, and was first used in the powerful CCASat solver as a tie breaker. In this paper, we propose three new scoring functions based on score_2. Despite their simplicity, these functions are very effective for solving random k-SAT with long clauses. The first function combines score and score_2, and the second one additionally integrates the diversification property "age". These two functions are used in developing a new SLS algorithm called CScoreSAT. Experimental results on large random 5-SAT and 7-SAT instances near phase transition show that CScoreSAT significantly outperforms previous SLS solvers. However, CScoreSAT cannot rival its competitors on random k-SAT instances at phase transition. We improve CScoreSAT for such instances by another scoring function which combines score_2 with age. The resulting algorithm HScoreSAT exhibits state-of-the-art performance on random k-SAT (k>3) instances at phase transition. We also study the computation of score_2, including its implementation and computational complexity.
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7

Frieze*, Alan, and Nicholas C. Wormald†. "Random k-Sat: A Tight Threshold For Moderately Growing k." Combinatorica 25, no. 3 (May 2005): 297–305. http://dx.doi.org/10.1007/s00493-005-0017-3.

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8

Friedman, Joel, Andreas Goerdt, and Michael Krivelevich. "Recognizing More Unsatisfiable Random k-SAT Instances Efficiently." SIAM Journal on Computing 35, no. 2 (January 2005): 408–30. http://dx.doi.org/10.1137/s009753970444096x.

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9

Boufkhad, Yacine, Olivier Dubois, Yannet Interian, and Bart Selman. "Regular Random k-SAT: Properties of Balanced Formulas." Journal of Automated Reasoning 35, no. 1-3 (August 3, 2006): 181–200. http://dx.doi.org/10.1007/s10817-005-9012-z.

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10

Nie, Guoxia, Daoyun Xu, Xiaofeng Wang, and Xi Wang. "The Phase Transition Analysis for the Random Regular Exact 2-(d, k)-SAT Problem." Symmetry 13, no. 7 (July 8, 2021): 1231. http://dx.doi.org/10.3390/sym13071231.

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In a regular (d,k)-CNF formula, each clause has length k and each variable appears d times. A regular structure such as this is symmetric, and the satisfiability problem of this symmetric structure is called the (d,k)-SAT problem for short. The regular exact 2-(d,k)-SAT problem is that for a (d,k)-CNF formula F, if there is a truth assignment T, then exactly two literals of each clause in F are true. If the formula F contains only positive or negative literals, then there is a satisfiable assignment T with a size of 2n/k such that F is 2-exactly satisfiable. This paper introduces the (d,k)-SAT instance generation model, constructs the solution space, and employs the method of the first and second moments to present the phase transition point d* of the 2-(d,k)-SAT instance with only positive literals. When d<d*, the 2-(d,k)-SAT instance can be satisfied with high probability. When d>d*, the 2-(d,k)-SAT instance can not be satisfied with high probability. Finally, the verification results demonstrate that the theoretical results are consistent with the experimental results.
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11

Achlioptas, Dimitris, and Yuval Peres. "The threshold for random $k$-SAT is $2^k\log 2-O(k)$." Journal of the American Mathematical Society 17, no. 4 (August 27, 2004): 947–73. http://dx.doi.org/10.1090/s0894-0347-04-00464-3.

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12

Vyas, Nikhil, and Ryan Williams. "On Super Strong ETH." Journal of Artificial Intelligence Research 70 (January 27, 2021): 473–95. http://dx.doi.org/10.1613/jair.1.11859.

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Multiple known algorithmic paradigms (backtracking, local search and the polynomial method) only yield a 2n(1-1/O(k)) time algorithm for k-SAT in the worst case. For this reason, it has been hypothesized that the worst-case k-SAT problem cannot be solved in 2n(1-f(k)/k) time for any unbounded function f. This hypothesis has been called the "Super-Strong ETH", modelled after the ETH and the Strong ETH. It has also been hypothesized that k-SAT is hard to solve for randomly chosen instances near the "critical threshold", where the clause-to-variable ratio is such that randomly chosen instances are satisfiable with probability 1/2. We give a randomized algorithm which refutes the Super-Strong ETH for the case of random k-SAT and planted k-SAT for any clause-to-variable ratio. For example, given any random k-SAT instance F with n variables and m clauses, our algorithm decides satisfiability for F in 2n(1-c*log(k)/k) time with high probability (over the choice of the formula and the randomness of the algorithm). It turns out that a well-known algorithm from the literature on SAT algorithms does the job: the PPZ algorithm of Paturi, Pudlak, and Zane (1999). The Unique k-SAT problem is the special case where there is at most one satisfying assignment. Improving prior reductions, we show that the Super-Strong ETHs for Unique k-SAT and k-SAT are equivalent. More precisely, we show the time complexities of Unique k-SAT and k-SAT are very tightly correlated: if Unique k-SAT is in 2n(1-f(k)/k) time for an unbounded f, then k-SAT is in 2n(1-f(k)/(2k)) time.
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13

Vyas, Nikhil, and Ryan Williams. "Results on a Super Strong Exponential Time Hypothesis." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 09 (April 3, 2020): 13700–13703. http://dx.doi.org/10.1609/aaai.v34i09.7125.

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All known SAT-solving paradigms (backtracking, local search, and the polynomial method) only yield a 2n(1−1/O(k)) time algorithm for solving k-SAT in the worst case, where the big-O constant is independent of k. For this reason, it has been hypothesized that k-SAT cannot be solved in worst-case 2n(1−f(k)/k) time, for any unbounded ƒ : ℕ → ℕ. This hypothesis has been called the “Super-Strong Exponential Time Hypothesis” (Super Strong ETH), modeled after the ETH and the Strong ETH. We prove two results concerning the Super-Strong ETH:1. It has also been hypothesized that k-SAT is hard to solve for randomly chosen instances near the “critical threshold”, where the clause-to-variable ratio is 2k ln 2 −Θ(1). We give a randomized algorithm which refutes the Super-Strong ETH for the case of random k-SAT and planted k-SAT for any clause-to-variable ratio. In particular, given any random k-SAT instance F with n variables and m clauses, our algorithm decides satisfiability for F in 2n(1−Ω( log k)/k) time, with high probability (over the choice of the formula and the randomness of the algorithm). It turns out that a well-known algorithm from the literature on SAT algorithms does the job: the PPZ algorithm of Paturi, Pudlak, and Zane (1998).2. The Unique k-SAT problem is the special case where there is at most one satisfying assignment. It is natural to hypothesize that the worst-case (exponential-time) complexity of Unique k-SAT is substantially less than that of k-SAT. Improving prior reductions, we show the time complexities of Unique k-SAT and k-SAT are very tightly related: if Unique k-SAT is in 2n(1−f(k)/k) time for an unbounded f, then k-SAT is in 2n(1−f(k)(1−ɛ)/k) time for every ɛ > 0. Thus, refuting Super Strong ETH in the unique solution case would refute Super Strong ETH in general.
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14

Perkins, Will. "Random k -SAT and the power of two choices." Random Structures & Algorithms 47, no. 1 (March 19, 2014): 163–73. http://dx.doi.org/10.1002/rsa.20534.

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15

Abramé, André, Djamal Habet, and Donia Toumi. "Improving configuration checking for satisfiable random k-SAT instances." Annals of Mathematics and Artificial Intelligence 79, no. 1-3 (June 4, 2016): 5–24. http://dx.doi.org/10.1007/s10472-016-9515-9.

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16

Dequen, Gilles, and Olivier Dubois. "An Efficient Approach to Solving Random k-sat Problems." Journal of Automated Reasoning 37, no. 4 (October 20, 2006): 261–76. http://dx.doi.org/10.1007/s10817-006-9025-2.

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17

Krzakala, Florent, Marc Mézard, and Lenka Zdeborová. "Reweighted Belief Propagation and Quiet Planting for Random K-SAT." Journal on Satisfiability, Boolean Modeling and Computation 8, no. 3-4 (May 1, 2014): 149–71. http://dx.doi.org/10.3233/sat190096.

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18

Hàn, Hiệp, Yury Person, and Mathias Schacht. "Note on strong refutation algorithms for random k-SAT formulas." Electronic Notes in Discrete Mathematics 35 (December 2009): 157–62. http://dx.doi.org/10.1016/j.endm.2009.11.027.

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19

Talagrand, Michel. "The high temperature case for the random K-sat problem." Probability Theory and Related Fields 119, no. 2 (February 2001): 187–212. http://dx.doi.org/10.1007/pl00008758.

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20

Alava, Mikko, John Ardelius, Erik Aurell, Petteri Kaski, Supriya Krishnamurthy, Pekka Orponen, and Sakari Seitz. "Circumspect descent prevails in solving random constraint satisfaction problems." Proceedings of the National Academy of Sciences 105, no. 40 (October 1, 2008): 15253–57. http://dx.doi.org/10.1073/pnas.0712263105.

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We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused algorithm in the sense that it focuses on variables occurring in unsatisfied clauses. We show by extensive numerical investigations that ChainSAT and other focused algorithms solve large K-SAT instances almost surely in linear time, up to high clause-to-variable ratios α; for example, for K = 4 we observe linear-time performance well beyond the recently postulated clustering and condensation transitions in the solution space. The performance of ChainSAT is a surprise given that by design the algorithm gets trapped into the first local energy minimum it encounters, yet no such minima are encountered. We also study the geometry of the solution space as accessed by stochastic local search algorithms.
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21

Xu, Ke, and Wei Li. "On the average similarity degree between solutions of random k-SAT and random CSPs." Discrete Applied Mathematics 136, no. 1 (January 2004): 125–49. http://dx.doi.org/10.1016/s0166-218x(03)00204-x.

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22

Achlioptas, Dimitris, and Cristopher Moore. "Random k‐SAT: Two Moments Suffice to Cross a Sharp Threshold." SIAM Journal on Computing 36, no. 3 (January 2006): 740–62. http://dx.doi.org/10.1137/s0097539703434231.

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23

GOERDT, ANDREAS, and TOMASZ JURDZISKI. "Some Results on Random Unsatisfiable k-Sat Instances and Approximation Algorithms Applied to Random Structures." Combinatorics, Probability and Computing 12, no. 3 (May 2003): 245–67. http://dx.doi.org/10.1017/s0963548303005637.

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24

Gamarnik, David, and Madhu Sudan. "Performance of Sequential Local Algorithms for the Random NAE-$K$-SAT Problem." SIAM Journal on Computing 46, no. 2 (January 2017): 590–619. http://dx.doi.org/10.1137/140989728.

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25

Zhou, Guangyan, and Rui Kang. "On the Lower Bounds of (1,0)-Super Solutions for Random k-SAT." International Journal of Foundations of Computer Science 30, no. 02 (February 2019): 247–54. http://dx.doi.org/10.1142/s0129054119500035.

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Super solution is a notion introduced to produce robust and stable solutions of combinatorial optimization and decision problems. We consider the [Formula: see text]-super solutions of random instances of [Formula: see text]-SAT, where a clause is satisfied if and only if there are at least two satisfied literals in this clause. By using an enhanced weighting scheme, we obtain better lower bounds that, if a random [Formula: see text]-CNF formula [Formula: see text] is [Formula: see text]-unsatisfiable with probability tending to 1 as [Formula: see text], then [Formula: see text] for [Formula: see text], respectively.
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26

Jabbour, Saïd, Jerry Lonlac, Lakhdar Saïs, and Yakoub Salhi. "Revisiting the Learned Clauses Database Reduction Strategies." International Journal on Artificial Intelligence Tools 27, no. 08 (December 2018): 1850033. http://dx.doi.org/10.1142/s0218213018500331.

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In this paper, we revisit an important issue of CDCL-based SAT solvers, namely the learned clauses database management policies. Our motivation takes its source from a simple observation on the remarkable performances of both random and size-bounded reduction strategies. We first derive a simple reduction strategy, called Size-Bounded Randomized strategy (in short SBR), that combines maintaining short clauses (of size bounded by k), while deleting randomly clauses of size greater than k. The resulting strategy outperform the state-of-the-art on SAT instances taken from the SAT competitions 2013 and 2018, and remains competitive on a broad range of SAT instances of the SAT Competition 2014. Reinforced by the interest of keeping short clauses, we propose several new dynamic variants, and we discuss their performance. We also propose different ways for adjusting dynamically the size-bounded parameter of the strategy.
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27

Achlioptas, D., H. Jia, and C. Moore. "Hiding Satisfying Assignments: Two are Better than One." Journal of Artificial Intelligence Research 24 (November 3, 2005): 623–39. http://dx.doi.org/10.1613/jair.1681.

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The evaluation of incomplete satisfiability solvers depends critically on the availability of hard satisfiable instances. A plausible source of such instances consists of random k-SAT formulas whose clauses are chosen uniformly from among all clauses satisfying some randomly chosen truth assignment A. Unfortunately, instances generated in this manner tend to be relatively easy and can be solved efficiently by practical heuristics. Roughly speaking, for a number of different algorithms, A acts as a stronger and stronger attractor as the formula's density increases. Motivated by recent results on the geometry of the space of satisfying truth assignments of random k-SAT and NAE-k-SAT formulas, we introduce a simple twist on this basic model, which appears to dramatically increase its hardness. Namely, in addition to forbidding the clauses violated by the hidden assignment A, we also forbid the clauses violated by its complement, so that both A and compliment of A are satisfying. It appears that under this "symmetrization" the effects of the two attractors largely cancel out, making it much harder for algorithms to find any truth assignment. We give theoretical and experimental evidence supporting this assertion.
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28

Antonopoulou, Hera. "Kolmogorov complexity based upper bounds for the unsatisfiability threshold of random k-SAT." Journal of Discrete Mathematical Sciences and Cryptography 23, no. 7 (June 9, 2020): 1431–38. http://dx.doi.org/10.1080/09720529.2020.1711602.

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29

Mo, Xiaoling, Daoyun Xu, and Xi Wang. "The Phase Transition Analysis for Random Regular Exact (s, c, k)—SAT Problem." IEEE Access 9 (2021): 26664–73. http://dx.doi.org/10.1109/access.2021.3057858.

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30

SUBRAMANI, K. "CASCADING RANDOM WALKS." International Journal of Foundations of Computer Science 16, no. 03 (June 2005): 599–622. http://dx.doi.org/10.1142/s0129054105003182.

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In this paper, we discuss a simple, Monte Carlo algorithm for the problem of checking whether a Quantified Boolean Formula (QBF) in Conjunctive Normal Form (CNF), with at most two literals per clause has a model. The term k-CNF is used to describe boolean formulas in CNF, with at most k literals per clause and the problem of checking whether a given k-CNF formula is satisfiable is called the k-SAT problem. A QBF is a boolean formula, accompanied by a quantifier string which imposes a linear ordering on the variables of that formula. The problem of finding a model for a QBF formula in CNF, with at at most k literals per clause is called the QkSAT problem. The QkSAT problem is PSPACE-complete, for k≥3. However, the Q2SAT problem can be decided in polynomial time; the graph-based procedure, discussed in [1], is the first such algorithm for this problem. This procedure requires the construction of a global implication graph, corresponding to the input formula and searching for certain paths in this graph. Hence the complete set of clauses must be part of the input. We propose an incremental, randomized approach for the Q2SAT problem that is essentially local in nature, in that the complete clausal set need not be provided at any time, in the presence of a verifier. We show that the randomized algorithm can be analyzed as a one-dimensional random walk, with one reflecting barrier and one absorbing barrier. On a Q2SAT instance with m clauses on n variables, our coin-flipping algorithm runs in time O(n2 · V(m, n)), where V(m, n) is the time required to verify that a given model satisfies the formula. Additionally, if the instance is satisfiable, the probability that our algorithm fails to find a model is less than one half. The design and analysis of a randomized algorithm for a problem, is important from both the theoretical and the practical perspectives. Randomized approaches tend to be simple and elegant, thereby making the process of checking correctness, effortless as well. The randomized approach discussed in this paper lays the groundwork for analyzing a number of problems related to 2CNF formulas and directed graphs. We remark that our work in this paper is the first randomized algorithm for a class of QBFs.
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31

ZHOU, HAIJUN. "CRITICALITY AND HETEROGENEITY IN THE SOLUTION SPACE OF RANDOM CONSTRAINT SATISFACTION PROBLEMS." International Journal of Modern Physics B 24, no. 18 (July 20, 2010): 3479–87. http://dx.doi.org/10.1142/s0217979210056013.

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Random constraint satisfaction problems are interesting model systems for spin-glasses and glassy dynamics studies. As the constraint density of such a system reaches certain threshold value, its solution space may split into extremely many clusters. In this work we argue that this ergodicity-breaking transition is preceded by a homogeneity-breaking transition. For random K-SAT and K-XORSAT, we show that many solution communities start to form in the solution space as the constraint density reaches a critical value αcm, with each community containing a set of solutions that are more similar with each other than with the outsider solutions. At αcm the solution space is in a critical state. The connection of these results to the onset of dynamical heterogeneity in lattice glass models is discussed.
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32

HOGG, TAD. "SINGLE-STEP QUANTUM SEARCH USING PROBLEM STRUCTURE." International Journal of Modern Physics C 11, no. 04 (June 2000): 739–73. http://dx.doi.org/10.1142/s0129183100000663.

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The structure of satisfiability problems is used to improve search algorithms for quantum computers and to reduce their required coherence times by using only a single coherent evaluation of problem properties. The structure of random k-SAT allows the determination of the asymptotic average behavior of these algorithms, showing they improve on the quantum algorithms, such as amplitude amplification, that ignore detailed problem structure but remain exponential for hard problem instances. Compared to good classical methods, the algorithm performs better, on average, for weakly and highly constrained problems, but worse for hard cases. The analytic techniques introduced here apply also to other quantum algorithms, supplementing the limited evaluation possible with classical simulations, and showing how quantum computing can use the ensemble properties of NP search problems.
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33

Badr, Hamada S., Benjamin F. Zaitchik, and Seth D. Guikema. "Application of Statistical Models to the Prediction of Seasonal Rainfall Anomalies over the Sahel." Journal of Applied Meteorology and Climatology 53, no. 3 (March 2014): 614–36. http://dx.doi.org/10.1175/jamc-d-13-0181.1.

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AbstractRainfall in the Sahel region of Africa is prone to large interannual variability, and it has exhibited a recent multidecadal drying trend. The well-documented social impacts of this variability have motivated numerous efforts at seasonal precipitation prediction, many of which employ statistical techniques that forecast Sahelian precipitation as a function of large-scale indices of surface air temperature (SAT) anomalies, sea surface temperature (SST), surface pressure, and other variables. These statistical models have demonstrated some skill, but nearly all have adopted conventional statistical modeling techniques—most commonly generalized linear models—to associate predictor fields with precipitation anomalies. Here, the results of an artificial neural network (ANN) machine-learning algorithm applied to predict summertime (July–September) Sahel rainfall anomalies using indices of springtime (April–June) SST and SAT anomalies for the period 1900–2011 are presented. Principal component analysis was used to remove multicollinearity between predictor variables. Predictive accuracy was assessed using repeated k-fold random holdout and leave-one-out cross-validation methods. It was found that the ANN achieved predictive accuracy superior to that of eight alternative statistical methods tested in this study, and it was also superior to that of previously published predictive models of summertime Sahel precipitation. Analysis of partial dependence plots indicates that ANN skill is derived primarily from the ability to capture nonlinear influences that multiple major modes of large-scale variability have on Sahelian precipitation. These results point to the value of ANN techniques for seasonal precipitation prediction in the Sahel.
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34

Maciejewski, Filip B., Flavio Baccari, Zoltán Zimborás, and Michał Oszmaniec. "Modeling and mitigation of cross-talk effects in readout noise with applications to the Quantum Approximate Optimization Algorithm." Quantum 5 (June 1, 2021): 464. http://dx.doi.org/10.22331/q-2021-06-01-464.

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Measurement noise is one of the main sources of errors in currently available quantum devices based on superconducting qubits. At the same time, the complexity of its characterization and mitigation often exhibits exponential scaling with the system size. In this work, we introduce a correlated measurement noise model that can be efficiently described and characterized, and which admits effective noise-mitigation on the level of marginal probability distributions. Noise mitigation can be performed up to some error for which we derive upper bounds. Characterization of the model is done efficiently using Diagonal Detector Overlapping Tomography – a generalization of the recently introduced Quantum Overlapping Tomography to the problem of reconstruction of readout noise with restricted locality. The procedure allows to characterize k-local measurement cross-talk on N-qubit device using O(k2klog(N)) circuits containing random combinations of X and identity gates. We perform experiments on 15 (23) qubits using IBM's (Rigetti's) devices to test both the noise model and the error-mitigation scheme, and obtain an average reduction of errors by a factor >22 (>5.5) compared to no mitigation. Interestingly, we find that correlations in the measurement noise do not correspond to the physical layout of the device. Furthermore, we study numerically the effects of readout noise on the performance of the Quantum Approximate Optimization Algorithm (QAOA). We observe in simulations that for numerous objective Hamiltonians, including random MAX-2-SAT instances and the Sherrington-Kirkpatrick model, the noise-mitigation improves the quality of the optimization. Finally, we provide arguments why in the course of QAOA optimization the estimates of the local energy (or cost) terms often behave like uncorrelated variables, which greatly reduces sampling complexity of the energy estimation compared to the pessimistic error analysis. We also show that similar effects are expected for Haar-random quantum states and states generated by shallow-depth random circuits.
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35

Alsaber, A., A. Al-Herz, J. Pan, K. Saleh, A. Al-Awadhi, W. Al-Kandari, E. Hasan, et al. "THU0556 MISSING DATA AND MULTIPLE IMPUTATION IN RHEUMATOID ARTHRITIS REGISTRIES USING SEQUENTIAL RANDOM FOREST METHOD." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 519.1–519. http://dx.doi.org/10.1136/annrheumdis-2020-eular.4838.

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Background:Missing data in clinical epidemiological researches violate the intention to treat principle,reduce statistical power and can induce bias if they are related to patient’s response to treatment. In multiple imputation (MI), covariates are included in the imputation equation to predict the values of missing data.Objectives:To find the best approach to estimate and impute the missing values in Kuwait Registry for Rheumatic Diseases (KRRD) patients data.Methods:A number of methods were implemented for dealing with missing data. These includedMultivariate imputation by chained equations(MICE),K-Nearest Neighbors(KNN),Bayesian Principal Component Analysis(BPCA),EM with Bootstrapping(Amelia II),Sequential Random Forest(MissForest) and mean imputation. Choosing the best imputation method wasjudged by the minimum scores ofRoot Mean Square Error(RMSE),Mean Absolute Error(MAE) andKolmogorov–Smirnov D test statistic(KS) between the imputed datapoints and the original datapoints that were subsequently sat to missing.Results:A total of 1,685 rheumatoid arthritis (RA) patients and 10,613 hospital visits were included in the registry. Among them, we found a number of variables that had missing values exceeding 5% of the total values. These included duration of RA (13.0%), smoking history (26.3%), rheumatoid factor (7.93%), anti-citrullinated peptide antibodies (20.5%), anti-nuclear antibodies (20.4%), sicca symptoms (19.2%), family history of a rheumatic disease (28.5%), steroid therapy (5.94%), ESR (5.16%), CRP (22.9%) and SDAI (38.0%), The results showed that among the methods used, MissForest gave the highest level of accuracy to estimate the missing values. It had the least imputation errors for both continuous and categorical variables at each frequency of missingness and it had the smallest prediction differences when the models used imputed laboratory values. In both data sets, MICE had the second least imputation errors and prediction differences, followed by KNN and mean imputation.Conclusion:MissForest is a highly accurate method of imputation for missing data in KRRD and outperforms other common imputation techniques in terms of imputation error and maintenance of predictive ability with imputed values in clinical predictive models. This approach can be used in registries to improve the accuracy of data, including the ones for rheumatoid arthritis patients.References:[1]Junninen, H.; Niska, H.; Tuppurainen, K.; Ruuskanen, J.; Kolehmainen, M. Methods for imputation ofmissing values in air quality data sets.Atmospheric Environment2004,38, 2895–2907.[2]Norazian, M.N.; Shukri, Y.A.; Azam, R.N.; Al Bakri, A.M.M. Estimation of missing values in air pollutiondata using single imputation techniques.ScienceAsia2008,34, 341–345.[3]Plaia, A.; Bondi, A. Single imputation method of missing values in environmental pollution data sets.Atmospheric Environment2006,40, 7316–7330.[4]Kabir, G.; Tesfamariam, S.; Hemsing, J.; Sadiq, R. Handling incomplete and missing data in water networkdatabase using imputation methods.Sustainable and Resilient Infrastructure2019, pp. 1–13.[5]Di Zio, M.; Guarnera, U.; Luzi, O. Imputation through finite Gaussian mixture models.ComputationalStatistics & Data Analysis2007,51, 5305–5316.Disclosure of Interests:None declared
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Post, R. L., and I. Klodos. "Interpretation of extraordinary kinetics of Na(+)-K(+)-ATPase by a phase change." American Journal of Physiology-Cell Physiology 271, no. 5 (November 1, 1996): C1415—C1423. http://dx.doi.org/10.1152/ajpcell.1996.271.5.c1415.

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We interpret at a molecular level an extraordinary response in the transient kinetics of the phosphointermediate of Na(+)-K(+)-ATPase (I. Klodos, R. L. Post, and B. Forbush III. J. Biol. Chem. 269: 1734-1743, 1994). The phosphointermediate comprises two principal states. The partition between these states varies with salt concentration. A jump in salt concentration changes the partition of some of the molecules more rapidly than they interconvert in a steady state at constant salt concentration. We propose that interconversion is limited by free volume in the lipid of the surrounding membrane. This lipid is partitioned into phases that vary with salt concentration. Free volume is larger at the interface between these phases than within the phases themselves. Na(+)-K(+)-ATPase molecules are distributed at random in the membrane. When the phase boundary moves in response to a jump in salt concentration, it crosses some Na+ -K+ -ATPase molecules, which transiently experience an increase in free volume of the surrounding lipid. Thus their phosphointermediate states equilibrate more rapidly than at a constant salt concentration. Functional and structural heterogeneity of Na(+)-K(+)-ATPase molecules is discussed.
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37

Ojha, Chandrakanta, Adele Fusco, and Innocenzo M. Pinto. "Interferometric SAR Phase Denoising Using Proximity-Based K-SVD Technique." Sensors 19, no. 12 (June 14, 2019): 2684. http://dx.doi.org/10.3390/s19122684.

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This paper addresses the problem of interferometric noise reduction in Synthetic Aperture Radar (SAR) interferometry based on sparse and redundant representations over a trained dictionary. The idea is to use a Proximity-based K-SVD (ProK-SVD) algorithm on interferometric data for obtaining a suitable dictionary, in order to extract the phase image content effectively. We implemented this strategy on both simulated as well as real interferometric data for the validation of our approach. For synthetic data, three different training dictionaries have been compared, namely, a dictionary extracted from the data, a dictionary obtained by a uniform random distribution in [ − π , π ] , and a dictionary built from discrete cosine transform. Further, a similar strategy plan has been applied to real interferograms. We used interferometric data of various SAR sensors, including low resolution C-band ERS/ENVISAT, medium L-band ALOS, and high resolution X-band COSMO-SkyMed, all over an area of Mt. Etna, Italy. Both on simulated and real interferometric phase images, the proposed approach shows significant noise reduction within the fringe pattern, without any considerable loss of useful information.
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38

Gharavi, M. A., R. Armiento, B. Alling, and P. Eklund. "Theoretical study of the phase transitions and electronic structure of (Zr0.5, Mg0.5)N and (Hf0.5, Mg0.5)N." Journal of Materials Science 56, no. 1 (October 1, 2020): 305–12. http://dx.doi.org/10.1007/s10853-020-05372-1.

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Abstract Rock-salt scandium nitride has gained interest due to its thermoelectric properties including a relatively high Seebeck coefficient. This motivates research for other semiconductor materials that exhibit similar electronic structure features as ScN. Using density functional theory calculations, we have studied disordered solid solutions of (Zr0.5, Mg0.5)N and (Hf0.5, Mg0.5)N using the special quasi-random structure model. The results show that within a mean-field approximation for the configurational entropy, the order–disorder phase transformation between the monoclinic LiUN2 prototype structure and the rock-salt cubic random alloy of these mentioned solid solutions occur at 740 K and 1005 K for (Zr0.5, Mg0.5)N and (Hf0.5, Mg0.5)N, respectively. The density-of-states for the two ternary compounds is also calculated and predicts semiconducting behavior with band gaps of 0.75 eV for (Zr0.5, Mg0.5)N and 0.92 eV for (Hf0.5, Mg0.5)N. The thermoelectric properties of both compounds are also predicted. We find that in the range of a moderate change in the Fermi level, a high Seebeck coefficient value at room temperature can be achieved.
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39

Liu, Jun, Supei Zhang, Zihan Xu, Siqi Sun, Aowen Xiao, and Zhuang Du. "Modeling method of prediction model for salt field ion concentration under solar thermal system using random forest." Thermal Science 23, no. 5 Part A (2019): 2623–30. http://dx.doi.org/10.2298/tsci181128151l.

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At present, the underground brine deposit of Lop Nor salt lake in Xinjiang, while is rich in solar energy resource and can be one high efficient solar thermal utilization area, has become an important potash production base in China. During the development of salt lake brine, the collection methods are different according to the concentration of ions in different locations. In order to solve the problems of low accuracy and high calculation cost in prediction of salt field ion concentration, a data mining method based on random forest is applied in this paper. To build the model, we collected K+, SO42?, Cl?, and other two kinds of ions, among which the features included the collection time, collection locality and the number of salt pond. We used several methods to train and test the sample data, evaluated the experimental results using a variety of performance metrics and compared it with other methods at the same time. The results revealed that the optimal random forest model yielded the mean square error and coefficient of determination values of 0.073 and 0.940, which performed relatively better than support vector machine and extremely randomized trees.
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HENDRAWAN, ARI YUNUS. "PENINGKATAN KINERJA ALGORITMA K MEANS DENGAN MENGGUNAKAN PARTICLE SWARM OPTIMIZATION DALAM PENGELOMPOKAN DATA PENYEDIAAN AKSES." Electro Luceat 6, no. 2 (November 3, 2020): 213–27. http://dx.doi.org/10.32531/jelekn.v6i2.245.

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Water is one of the things that plays a very important role in human survival, because the Indonesian government has a community-based water supply and sanitation (PAMSIMAS) program, so that all the programs run well need a regional status grouping technique in this thesis. with the K-means algorithm. K-means is a partition algorithm that aims to divide the data into the specified number of clusters, the results of the K means algorithm depend on the selection of the initial klater center but problems that often occur when selecting the initial centroid are randomly drawn from the solution. from the grouping is not quite right. To overcome this problem the author wants to use the PSO algorithm in the initial centroid selector for the K-means algorithm, in this study also compared the selection of the first 3 centroids according to random, second according to government standards the value of high, medium and low drinking water quality then the third method proposed by the PSO algorithm was then tested with Davies Bouldin Index. From the test results, the K-means method with the selection of random initial centroid with a value of 0.208856082, the K-means method with the selection of centroids in accordance with government standards about SAM conditions of 0.280077 and the best selection method is K-means PSO 0, 08383. So testing the PAMSIMAS data using K-means PSO found that the method was more optimal.
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41

Hendriksen, Marieke AH, Joop MA van Raaij, Johanna M. Geleijnse, Caroline Wilson-van den Hooven, Marga C. Ocké, and Daphne L. van der A. "Monitoring salt and iodine intakes in Dutch adults between 2006 and 2010 using 24 h urinary sodium and iodine excretions." Public Health Nutrition 17, no. 7 (June 5, 2013): 1431–38. http://dx.doi.org/10.1017/s1368980013001481.

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AbstractObjectiveTo monitor the effectiveness of salt-reduction initiatives in processed foods and changes in Dutch iodine policy on Na and iodine intakes in Dutch adults between 2006 and 2010.DesignTwo cross-sectional studies among adults, conducted in 2006 and 2010, using identical protocols. Participants collected single 24 h urine samples and completed two short questionnaires on food consumption and urine collection procedures. Daily intakes of salt, iodine, K and Na:K were estimated, based on the analysis of Na, K and iodine excreted in urine.SettingDoetinchem, the Netherlands.SubjectsMen and women aged 19 to 70 years were recruited through random sampling of the Doetinchem population and among participants of the Doetinchem Cohort Study (2006:n317, mean age 48·9 years, 43 % men; 2010:n342, mean age 46·2 years, 45 % men).ResultsWhile median iodine intake was lower in 2010 (179 μg/d) compared with 2006 (257 μg/d;P< 0·0001), no difference in median salt intake was observed (8·7 g/d in 2006v. 8·5 g/d in 2010,P= 0·70). In 2006, median K intake was 2·6 g/dv. 2·8 g/d in 2010 (P< 0·01). In this 4-year period, median Na:K improved from 2·4 in 2006 to 2·2 in 2010 (P< 0·001).ConclusionsDespite initiatives to lower salt in processed foods, dietary salt intake in this population remains well above the recommended intake of 6 g/d. Iodine intake is still adequate, although a decline was observed between 2006 and 2010. This reduction is probably due to changes in iodine policy.
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42

Dvořák, J., and J. Gorham. "Methodology of gene transfer by homoeologous recombination into Triticum turgidum: transfer of K+/Na+ discrimination from Triticum aestivum." Genome 35, no. 4 (August 1, 1992): 639–46. http://dx.doi.org/10.1139/g92-096.

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Triticum aestivum (2n = 6x = 42) differs from T. turgidum (2n = 4x = 28) by superior ability to exclude Na+ and accumulate K+ under salt stress. Chromosome 4D has a major affect on the enhancement of this trait in T. aestivum. To transfer this trait to T. turgidum, T. turgidum chromosome 4B was targeted for homoeologous recombination with chromosome 4D in the genetic background of T. turgidum, utilizing recessive mutant ph1c to enhance meiotic heterogenetic chromosome pairing. Since the basis of the genetic control of this trait by chromosome 4D was not known, a large population of random recombinant lines involving the alien chromosome and the wheat chromosome had to be produced. It was hypothesized that assaying lines in such a population for the trait would facilitate identification of those in which the gene or genes controlling the trait were incorporated into the T. turgidum chromosome. Forty lines with recombinant chromosomes were obtained. Thirty-nine recombination events involving chromosome 4D involved the targeted chromosome 4B. The ratio of K+/Na+ in leaves of plants grown under salt stress was determined for 27 lines. Nine lines showed enhanced K+/Na+ ratios. Evidence is presented that this trait is controlled by a single gene locus, designated here as Kna1. The locus is distal to the subterminal C-band in the long arm of chromosome 4D.Key words: wheat, linkage map distortion, salt stress tolerance.
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43

Fanani, Nurul Zainal, Adri Gabriel Sooai, Surya Sumpeno, and Mauridhi Hery Purnomo. "Penentuan Kemampuan Motorik Halus Anak dari Proses Menulis Hanacaraka Menggunakan Random Forest." Jurnal Nasional Teknik Elektro dan Teknologi Informasi 9, no. 2 (May 29, 2020): 148–54. http://dx.doi.org/10.22146/jnteti.v9i2.153.

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Penilaian Kemampuan Motorik Halus (KMH) untuk anak pada awal usia sekolah sangat penting untuk mendapatkan informasi tentang kesiapan sekolah anak. Selama ini proses pengukuran KMH dilakukan dengan cara observasi pada anak, baik secara langsung maupun dari hasil sketsa atau hasil tulisan anak. Proses pengamatan ini sangat bergantung pada persepsi pengamat, sehingga dapat mengakibatkan kurangnya objektivitas dalam penilaian. Makalah ini bertujuan untuk menentukan KMH anak menggunakan aksara jawa (Hanacaraka). Makalah ini mengembangkan metode baru untuk menentukan KMH anak sekolah dasar dari proses menulis aksara jawa. Sistem melakukan perekaman data secara langsung pada saat anak menulis aksara jawa. Pengambilan data rekaman proses menulis melibatkan empat belas siswa kelas 1 dan kelas 2 dari tiga sekolah dasar di Kabupaten Jember. Proses perekaman data dari setiap siswa menghasilkan data raw yang cukup besar. Oleh karena itu, digunakan metode klasifikasi random forest karena metode ini dapat melakukan proses klasifikasi pada data dalam jumlah yang besar dengan menggabungkan beberapa pohon keputusan. Metode klasifikasi lain, termasuk naïve Bayes dan k-NN, juga diuji sebagai perbandingan. Hasil uji coba menunjukkan bahwa metode klasifikasi random forest merupakan metode terbaik dalam penelitian ini, yaitu dengan akurasi mencapai 98,7%.
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44

Dessy Kusumaningrum and Elly Matul Imah. "Studi Komparasi Algoritma Klasifikasi Mental Workload Berdasarkan Sinyal EEG." Jurnal Sistem Cerdas 3, no. 2 (August 31, 2020): 133–43. http://dx.doi.org/10.37396/jsc.v3i2.69.

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Kondisi psikologis dan fisik manusia dapat memengaruhi proses berpikir. Apabila kondisi individu mengalami kelelahan, maka dapat memengaruhi penurunan tingkat produktivitas maupun penurunan proses berpikir yang menyebabkan timbulnya mental workload. Workload yang dimiliki harus seimbang terhadap kemampuan dan keterbatasan yang dimiliki. Mental workload yang berlebih berdampak buruk bagi individu karena menimbulkan penurunan produktivitas kerja. Perangkat khusus yang dapat digunakan untuk mengetahui tingkat mental workload seorang individu adalah Electroencephalogram (EEG). EEG adalah perangkat khusus yang digunakan untuk mengukur sinyal potensi listrik dari otak. Dataset yang digunakan dalam penelitian ini adalah STEW: Simultaneous Task EEG Dataset dengan 45 subjek. Dalam penelitian ini, telah dilakukan studi komparasi algoritma Random Forest, K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), dan Support Vector Machine (SVM) untuk klasifikasi mental workload berdasarkan sinyal EEG. Studi dilakukan untuk menentukan algoritma terbaik dalam klasifikasi dilihat dari segi nilai akurasi dan penggunaan memori saat proses klasifikasi. Dataset telah melalui beberapa tahapan, diantaranya pra-pemrosesan data, ekstraksi fitur, dan proses klasifikasi. Pra-pemrosesan data menerapkan pembagian data menjadi beberapa chunk. Untuk mendapatkan ciri dalam ekstraksi fitur, diterapkan metode Principal Component Analysis (PCA). Pada proses klasifikasi menggunakan pendekatan k-fold cross validation. Hasil studi penelitian ini adalah algoritma terbaik dari sisi akurasi adalah algoritma KNN, algoritma terbaik dari sisi waktu pembuatan model adalah algoritma Random Forest, serta algoritma terbaik dari sisi penggunaan memori adalah algoritma MLP.
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45

Tazaki, Kazue, and W. S. Fyfe. "Primitive clay precursors formed on feldspar." Canadian Journal of Earth Sciences 24, no. 3 (March 1, 1987): 506–27. http://dx.doi.org/10.1139/e87-051.

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High-resolution transmission electron microscopy of clay formation on K-feldspar has revealed the existence of intermediate states between feldspar and crystalline clay products. During the earliest weathering stages of K-feldspar, a primitive clay precursor forms on the feldspar surface that is spotted by ion oxides. This reactive iron is incorporated into the primitive clay precursors, which have an ultrathin 150–200 Å (1 Å = 0.1 nm) circular form and 14–20 Å lattice images or long, curled fiber forms with varied lattice image spacings. The electron diffraction patterns of primitive clay precursors show diffuse rings at 2.65, 2.04, and 1.51 Å, suggesting low crystallinity, random orientation, and partial inheritance of the original structure. EDX step scanning analysis showed that the major-element concentrations of Si, Al, and K tend to decrease from unaltered parts to altered parts of precursors with substantial increase in Fe. Auger depth profiling showed the thickness of the primitive clay layers is 150–300 Å. The primitive clay precursors may well precede formation of spheroidal particles of halloysite, squat cylinders of halloysite or hexagonal crystalline, and tabuler halloysite (7 Å). SEM, XRD, SIMS, and SAM data support the TEM results.
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46

Zhang, Hongming, Yongping Wang, and Chuang Peng. "Ameliorated mean adaptive median filtering algorithm." E3S Web of Conferences 118 (2019): 02069. http://dx.doi.org/10.1051/e3sconf/201911802069.

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Aiming at the problem that the quality of infrared image decreases due to the large amount of random noise in the process of collection and transmission of infrared image of electrical equipment, and the accuracy of automatic detection of electrical equipment decreases, based on the traditional adaptive median filter algorithm, the adaptive median filter is analyzed, which can filter only the salt and pepper noise below 25%. An improved mean adaptive median filtering algorithm is proposed to overcome the shortcomings of wave effect. Firstly, the filtering window is selected according to the decision setting condition, and then it is judged whether the K-mean value near the center point is a noise point, and if so, the window is increased, otherwise the average value is output. Finally, it is judged whether the value of the current pixel point is noise, and if so, the average value is output, otherwise, the current pixel value is output. The experimental results show that the algorithm can effectively filter salt and pepper noise and Gauss noise, while maintaining the image sharpness, and has good filtering performance on PSNR and MSE indicators.
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47

Moritz, Karen M., Andrew Jefferies, E. Marelyn Wintour, and Miodrag Dodic. "Fetal renal and blood pressure responses to steroid infusion after early prenatal treatment with dexamethasone." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 288, no. 1 (January 2005): R62—R66. http://dx.doi.org/10.1152/ajpregu.00282.2004.

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Maternal infusion of dexamethasone for 48 h early in gestation results in upregulation of mRNA for mineralocorticoid and glucocorticoid (MR and GR) receptors and angiotensin II receptors in ovine fetal kidneys late in gestation. This study sought to determine whether dexamethasone exposure results in changes in renal function and blood pressure responsiveness to infused cortisol or aldosterone in the late-gestation fetus. Merino ewes carrying single fetuses were infused with isotonic saline (Sal; n = 9) or dexamethasone (Dex, 0.48 mg/h; n = 10) for 48 h between days 26 and 28 of gestation (term = 150 days). At 115–122 days, renal function and blood pressure were measured in fetuses during a 4-h infusion of saline, cortisol (100 μg/h), or aldosterone (5 μg/h). Infusions were given in random order at least 2 days apart. Basal blood pressure and renal function were similar in Sal and Dex groups and did not change over the course of saline infusion. Cortisol infusion caused similar increases in blood pressure, urine flow, and glomerular filtration rate (GFR) in the groups. Aldosterone infusion caused a significantly different GFR response between the groups [ P(treatment × time) < 0.05], but increase in K excretion and decrease in Na-to-K ratio were similar in the groups. The similar results obtained with cortisol and aldosterone infusion suggest no increased renal functional maturity to those hormones after early prenatal dexamethasone exposure. This suggests that changes in mRNA for MR and GR in kidneys of dexamethasone-exposed fetuses do not result in functional differences and highlights the renin-angiotensin system, as reported previously, as more important in this model.
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48

Hendrasto, Aryono, Johan Arifin, and Mohamad Sofyan Harahap. "Pengaruh Pemberian Ketorolak 30 mg Intravena pada Penderita dengan Anestesi Spinal Terhadap Fungsi Pembekuan Darah : Protrombin Time, Partial Tromboplastin Time with Kaolin." JAI (Jurnal Anestesiologi Indonesia) 1, no. 1 (October 11, 2013): 26. http://dx.doi.org/10.14710/jai.v1i1.6021.

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Latar belakang: Saat ini penggunaan ketorolak sebagai analgesik meningkat karena sifatnya yang menguntungkan untuk mempercepat ambulatory pasien, namun mempunyai efek samping memperpanjang waktu perdarahan (bleeding time) melalui gangguan fungsi trombosit. Perdarahan juga dapat disebabkan gangguan pembuluh darah dan fungsi koagulasi. Ada hubungan saling terkait antara fungsi trombosit dan fungsi koagulasi.Tujuan: Membuktikan bahwa pemberian ketorolak 30 mg intravena pada penderita dengan spinal anestesi menyebabkan pemanjangan fungsi koagulasi (protrombin time dan partial tromboplastin time)Metode: Merupakan penelitian eksperimental dengan randomized post test only controlled group pada 30 penderita yang akan menjalani operasi elektif dengan anestesi spinal. Penderita secara random dibagi menjadi dua kelompok, yaitu kelompok P yang mendapat ketorolak 30 mg iv dan kelompok K yang mendapat placebo ((NaCl 0,9%). Pemeriksaan PT, PTT dilakukan menjelang operasi dan 60 menit setelah pemberian ketorolak atau placebo. Hasilnya dinilai dengan menggunakan uji statistikparametric T- test, dengan derajat kemaknaan p<0,05.Hasil: Uji Independent T-test variable PT post tindakan dan PTTK post tindakan antara kelompok P dan kelompok K menunjukkan perbedaan yang tidak bermakna (p>0,05). Uji Paired T-test, untuk variabel PT pre tindakan dan PT post tindakan pada kelompok P menunjukkan perbedaan yang tidak bermakna (p=0,237). Untuk variable PTTK pre tindakan dan PTTK post tindakan pada kelompok P menunjukkan perbedaan bermakna (p=0,029). Uji Paired T-test, untuk variabel PT pre tindakan dan PT post tindakan pada kelompok K menunjukkan perbedaan yang tidak bermakna(p=0,062). Untuk variabel PTTK pre tindakan dan PTTK post tindakan pada kelompok K menunjukkan perbedaan tidak bermakna(p=0,160).Kesimpulan: Pemberian dosis tunggal ketorolak 30 mg intravena pada penderita dengan anestesi spinal tidak berpengaruh terhadap fungsi koagulasi jalur ekstrinsik (PT) tapi akan memperpanjang fungsi koagulasi jalur intrinsik (PTTK) namun pemanjangan ini masih dalam batas normal atau tidak nampak secara klinis.
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Ding, Yu, Wan Zhang, Xingqiang Zhao, Liwen Zhang, and Fei Yan. "A hybrid random forest method fusing wavelet transform and variable importance for the quantitative analysis of K in potassic salt ore using laser-induced breakdown spectroscopy." Journal of Analytical Atomic Spectrometry 35, no. 6 (2020): 1131–38. http://dx.doi.org/10.1039/d0ja00010h.

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50

Ćwiklińska-Jurkowska, Małgorzata. "Gene selection ensembles and classifier ensembles for medical diagnosis." Biometrical Letters 56, no. 2 (December 1, 2019): 117–38. http://dx.doi.org/10.2478/bile-2019-0007.

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SummaryThe usefulness of combining methods is examined using the example of microarray cancer data sets, where expression levels of huge numbers of genes are reported. Problems of discrimination into two groups are examined on three data sets relating to the expression of huge numbers of genes. For the three examined microarray data sets, the cross-validation errors evaluated on the remaining half of the whole data set, not used earlier for the selection of genes, were used as measures of classifier performance. Common single procedures for the selection of genes—Prediction Analysis of Microarrays (PAM) and Significance Analysis of Microarrays (SAM)—were compared with the fusion of eight selection procedures, or of a smaller subset of five of them, excluding SAM or PAM. Merging five or eight selection methods gave similar results. Based on the misclassification rates for the three examined microarray data sets, for any examined ensemble of classifiers, the combining of gene selection methods was not superior to single PAM or SAM selection for two of the examined data sets. Additionally, the procedure of heterogeneous combining of five base classifiers—k-nearest neighbors, SVM linear and SVM radial with parameter c=1, shrunken centroids regularized classifier (SCRDA) and nearest mean classifier—proved to significantly outperform resampling classifiers such as bagging decision trees. Heterogeneously combined classifiers also outperformed double bagging for some ranges of gene numbers and data sets, but merging is generally not superior to random forests. The preliminary step of combining gene rankings was generally not essential for the performance for either heterogeneously or homogeneously combined classifiers.
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