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An ensemble of models of the acute inflammatory response to bacterial lipopolysaccharide in rats: Results from parameter space reduction

Silvia Daun, Jonathan Rubin, Yoram Vodovotz, Anirban Roy, Robert Parker, Gilles Clermont
2008 Journal of Theoretical Biology  
A cluster analysis of the ensemble of models showed the existence of a continuum of acceptable models, characterized by compensatory mechanisms and parameter changes.  ...  terms of fit to experimental data.  ...  Clustering result on 296 models ARTICLE IN PRESS Compensatory mechanisms To investigate which of the remaining 18 parameters of the reduced model are responsible for compensating for the diverse damage  ... 
doi:10.1016/j.jtbi.2008.04.033 pmid:18550083 fatcat:i5afdkxeufhi7ndshj6cteovgy

Comments on "Total and fractional densities of states from caloric relations" by S. F. Chekmarev and S. V. Krivov, Phys. Rev. E 57 2445 (1998) [article]

Ikhtier Holmamatovich Umirzakov
2020 arXiv   pre-print
in the paper does not represent the microcanonical ensemble of clusters.  ...  We showed also that the total and fractional densities of states obtained in the paper from caloric relations are not equal to that of microcanonical ensemble of clusters, the ensemble of clusters used  ...  Hence, in order to describe the data obtained by classical mechanical MD simulations it is necessary to put for all isomers in Eqs. (3), (4a) and (5a). So, [1] .  ... 
arXiv:2001.10166v1 fatcat:khhzkiqgxvaf5i5etd2gpecnuy

Racs based Weight Optimization and Layered Clustering-based ECOC

Deepak Rajak, Roopam Gupta, Sanjeev Sharma
2015 International Journal of Computer Applications  
The first step employs the layered clustering-based approach [1].  ...  In propose work instead of weighted optimization technique we would further like to work on recursive ant optimization scheme for classification Keywords Classifier ensemble, error correcting output codes  ...  For this problem, in [ Layered Clustering-Based Approach: The layered clustering-based (LC) approach [1] is a special classifier ensemble.  ... 
doi:10.5120/ijca2015906889 fatcat:fxsqw6plq5cjzeyuidf7gevshu

A review on data stream classification approaches

Sajad Homayoun, Marzieh Ahmadzadeh
2016 Journal of Advanced Computer Science & Technology  
Similar to data mining, data stream mining includes classification, clustering, frequent pattern mining etc. techniques; the special focus of this paper is on classification methods invented to handle  ...  Early methods of data stream classification needed all instances to be labeled for creating classifier models, but there are some methods (Semi-Supervised Learning and Active Learning) in which unlabeled  ...  Zhang et al. proposed an ensemble model in [28] which uses a combination of classification and clustering for mining data streams.  ... 
doi:10.14419/jacst.v5i1.5225 fatcat:p6uhbyskwjbdpc5xoezpznctrq

An automated approach to network features of protein structure ensembles

Moitrayee Bhattacharyya, Chanda R. Bhat, Saraswathi Vishveshwara
2013 Protein Science  
The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation=interaction energy in PSN-Ensemble brings in dynamical=chemical knowledge into the network representation.  ...  Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active=inactive states of b2-adrenergic receptor and the ternary tRNA complexes of tyrosyl  ...  The authors also thank Vasundhara Gadiyaram for the help provided in creating the webpage for PSN-Ensemble. The fellowship for CRB was supported by Microsoft-Research grant.  ... 
doi:10.1002/pro.2333 pmid:23934896 pmcid:PMC3795498 fatcat:qmwqltcsjrcstlirlp4fzurd3q

Detecting anomalies in cellular networks using an ensemble method

Gabriela F. Ciocarlie, Ulf Lindqvist, Szabolcs Novaczki, Henning Sanneck
2013 Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013)  
This paper focuses on the problem of cell anomaly detection, addressing partial and complete degradations in cell-service performance, and it proposes an adaptive ensemble method framework for modeling  ...  The results, generated using real cellular network data, suggest that the proposed ensemble method automatically and significantly improves the detection quality over univariate and multivariate methods  ...  ACKNOWLEDGMENT We thank Lauri Oksanen, Kari Aaltonen, Richard Fehlmann, Christoph Frenzel, Péter Szilágyi, Michael Freed, Ken Nitz, and Christopher Connolly for their contributions.  ... 
doi:10.1109/cnsm.2013.6727831 dblp:conf/cnsm/CiocarlieLNS13 fatcat:bco36v7o7zeorlcdw4hyymtsey

Histopathological Image Classification with Gaussian Process Experts

Gang Zhang, Yiyu Lin, Huadong Lai, Dong Lin
2017 ICIC Express Letters  
The main idea is that a set of GP experts is initialized and improved with a data point selection strategy, through which a data point is assigned to a GP expert by evaluating how close it is to the representation  ...  We propose a classification method for histopathological image based on Gaussian process (GP) experts.  ...  Meanwhile, for the ensemble mechanism of the trained GP experts, we will study an optimal algorithm which can balance the concerning criteria for ensemble. Figure 1 . 1 Figure 1.  ... 
doi:10.24507/icicel.11.08.1299 fatcat:4jzsr6xquja4zmu2k3slzrx6iq

An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components

Sergii Babichev
2018 Data  
The information technology is presented as a structural block-chart, which contains all stages of the studied data processing.  ...  The hybrid model of objective clustering based on the SOTA algorithm and the technology of gene regulatory networks reconstruction have been investigated to evaluate the stability to the level of the noise  ...  Creation of the plots of complex balance criterion versus the weigh coefficient value for both the data without noise and the data with different levels of noise component.  ... 
doi:10.3390/data3040048 fatcat:lyo2ezu6hngvbayrjhhdjfsqnu

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Lars Skjærven, Xin-Qiu Yao, Guido Scarabelli, Barry J Grant
2014 BMC Bioinformatics  
for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis.  ...  Results: Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package.  ...  We acknowledge the University of Bergen (LS) and University of Michigan (XY, GS and BJG) for funding.  ... 
doi:10.1186/s12859-014-0399-6 pmid:25491031 pmcid:PMC4279791 fatcat:q2qsknwvbzhx7kymw57jx76s34

Semi-supervised learning in nonstationary environments

Gregory Ditzler, Robi Polikar
2011 The 2011 International Joint Conference on Neural Networks  
In this contribution, we describe an ensemble of classifiers based approach that takes advantage of both labeled and unlabeled data in addressing concept drift: available labeled data are used to generate  ...  Independently from concept drift research, semi-supervised approaches have been developed for learning from (limited) labeled and (abundant) unlabeled data; however, such approaches have been largely absent  ...  In another approach, the same authors ensemble algorithms for combining classifiers and clusters for learning from data streams [28] . III.  ... 
doi:10.1109/ijcnn.2011.6033578 dblp:conf/ijcnn/DitzlerP11 fatcat:hmbacxyhpvbyjo65ndpj6fgr5a

Incremental Learning: Areas and Methods – A Survey

Prachi Joshi
2012 International Journal of Data Mining & Knowledge Management Process  
While the areas of applications in data mining are growing substantially, it has become extremely necessary for incremental learning methods to move a step ahead.  ...  The tremendous growth of unlabeled data has made incremental learning take up a big leap.  ...  Bayesian learning, Resource Allocation Network Medical Image segmentation/ Sports video SVM, Ensemble methods, Dynamic weighing Optical character/ Text document Concept drift, Ensemble methods Weather  ... 
doi:10.5121/ijdkp.2012.2504 fatcat:vv4go3hvvngalerdo6jxjdo6la

Graph-based Selective Outlier Ensembles [article]

Hamed Sarvari, Carlotta Domeniconi, Giovanni Stilo
2018 arXiv   pre-print
An ensemble technique is characterized by the mechanism that generates the components and by the mechanism that combines them.  ...  Of the family of ensemble methods, outlier ensembles are the least studied. Only recently, the selection problem for outlier ensembles has been discussed.  ...  Introduction An ensemble technique is characterized by the mechanism that generates the components and by the mechanism that combines them.  ... 
arXiv:1804.06378v1 fatcat:aktizlbobrhfveodhqnccm6uri

Impact of Variable Size Chunk Data on Classifier Performance using Ensemble Techniques

Leena Deshpande
2020 International Journal of Advanced Trends in Computer Science and Engineering  
In recent times, enormous growth of real-world data and its usage raised an issue of processing data for extracting meaningful patterns.  ...  The combine approach of variable sized sample and weighted Ensemble classifiers not only detect the change in the concept but also applied for drift detection.  ...  [6] where an optimal clustering algorithm is applied on dataset and further given to classifier for optimum solution using Ensemble clustering method.  ... 
doi:10.30534/ijatcse/2020/185932020 fatcat:sf74oymapjhadli22w27dglc6e

A Systematic Review of Ensemble Techniques for Software Defect and Change Prediction

Megha Khanna
2022 e-Informatica Software Engineering Journal  
Conclusion: The results of the review ascertain the need of more studies to propose, assess, validate, and compare various categories of ensemble techniques for diverse applications in SDP/SCP such as  ...  They were also found effective in several applications such as their use as a learning algorithm for developing SDP/SCP models and for addressing the class imbalance issue.  ...  Sugandha Gupta for helping in data extraction and quality analysis of the candidate studies.  ... 
doi:10.37190/e-inf220105 fatcat:5kolnxcfmzeltmb4iokv6abbny

Optimization of Basic Clustering for Ensemble Clustering: An Information-theoretic Perspective

Wei Liang, Yuanjian Zhang, Jianfeng Xu, Deyu Lin
2019 IEEE Access  
The current research on ensemble clustering mainly focuses on integration strategies, but the attention regarding the measurement and optimization of basic cluster is less emphasized.  ...  Both mechanism executed repeatedly until either non-decrement of basic clusters occurred or maximum iteration count reached.  ...  ACKNOWLEDGMENT The authors would like to thank all the editors and anonymous reviews for their professional comments and suggestions, which are of great importance to improve the quality of this paper.  ... 
doi:10.1109/access.2019.2950159 fatcat:cuanpqetyzhmhjc4yhbm5h2vmi
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