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Intrusion Detection System- Via Fuzzy Artmap in Addition with Advance Semi Supervised Feature Selection

Swati Sonawale, Roshani Ade
2015 International Journal of Data Mining & Knowledge Management Process  
IDS technology is one of the significant tools used now-a-days, to counter such threat.  ...  Feature selection, as an active research area in decreasing dimensionality, eliminating unrelated data, developing learning correctness, and improving result unambiguousness.  ...  ACKNOWLEDGMENT Sincerely thank to all anonymous researchers for providing us such helpful opinion, findings, conclusions and recommendations. Also thank to guide Prof.  ... 
doi:10.5121/ijdkp.2015.5303 fatcat:gvxqtef35reuljb7odyvkbbuui

Dimensionality Reduction: An Effective Technique for Feature Selection

Swati ASonawale, Roshani Ade
2015 International Journal of Computer Applications  
By reducing the unrelated (irrelevant) and unnecessary features related to data, or by means of effectively merging original features to produce a smaller set of feature with more discriminative control  ...  In this research we have introduced a new method for dealing with the problem of dimensionality reduction.  ...  To achieve this, a feature evaluation criterion is used with a search strategy to identify the relevant features.  ... 
doi:10.5120/20535-2893 fatcat:f2uzmepx2fbgfi5hug5d4gzn7y

Querying Biological Sequences Docking Using Different Constraint Programming's: a Survey

B.Mallikarjuna Reddy, P Chandrasekhar, M.Ramakrishna Reddy
2015 International Journal of Computer Trends and Technology  
Different numbers of soft computing tools are available in market that is run based on data mining domain.  ...  In mixed data extract the useful biological sequences data with subgroup discovery iterative genetic algorithm, Cluster based fuzzy genetic algorithm mining framework, hierarchical fuzzy rule based systems  ...  Cluster Based Fuzzy Genetic Mining: Input: body n number of transactions, a set of items (m), identifies the linguistic information, apply the k-means clustering, select the population size (p), perform  ... 
doi:10.14445/22312803/ijctt-v22p110 fatcat:ag36qn6m4jdkhlakxvrbbisyma

Privacy-preserving data mining: A feature set partitioning approach

Nissim Matatov, Lior Rokach, Oded Maimon
2010 Information Sciences  
In privacy-preserving data mining (PPDM), a widely used method for achieving data mining goals while preserving privacy is based on k-anonymity.  ...  Guided by classification accuracy and k-anonymity constraints, the proposed data mining privacy by decomposition (DMPD) algorithm uses a genetic algorithm to search for optimal feature set partitioning  ...  Also we would like to acknowledge E. Zitzler for providing information about SPEA-II selection algorithm for GA-based multiobjective optimization. Many thanks are owed to Arthur Kemelman.  ... 
doi:10.1016/j.ins.2010.03.011 fatcat:lkyq2ufvbvbaxmqwjn7w63dl2a

Guest Editorial: Global modeling using local patterns

Johannes Fürnkranz, Arno Knobbe
2010 Data mining and knowledge discovery  
comments on the submitted papers contributed to this final selection of papers.  ...  Acknowledgements We would like to thank all authors who submitted their work to this special issue (in particular to those whose fine works did eventually not make the cut) and our reviewers, whose careful  ...  Feature selection Once the data source is transformed into a feature base, the feature selection phase (Guyon and Elisseeff 2003) is responsible for selecting a subset of these features (the mining base  ... 
doi:10.1007/s10618-010-0169-7 fatcat:sskra5hm7jfnfm4qpzxshf6doa

Semi-supervised Clustering of Graph Objects: A Subgraph Mining Approach [chapter]

Xin Huang, Hong Cheng, Jiong Yang, Jeffery Xu Yu, Hongliang Fei, Jun Huan
2012 Lecture Notes in Computer Science  
We derive an upper bound of the objective function based on which, a branch-and-bound algorithm is proposed to speedup subgraph mining.  ...  We design an objective function which incorporates the constraints to guide the subgraph feature mining and selection process.  ...  features based on both constraint and unconstraint graphs.  ... 
doi:10.1007/978-3-642-29038-1_16 fatcat:6bahaz6rbfcjnmtyyfdo2pcga4

Tackling Incompleteness in Information Extraction – A Complementarity Approach [chapter]

Christina Feilmayr
2012 Lecture Notes in Computer Science  
This research work integrates data mining and information extraction methods into a single complementary approach in order to benefit from their respective advantages and reduce incompleteness in information  ...  Methods such as emerging data mining techniques that help to overcome this incompleteness by obtaining new, additional information are consequently needed.  ...  Based on the requirements and problem analysis, several incompleteness types are identified and the available data mining methods classified accordingly. Conceptual Design and Method Selection.  ... 
doi:10.1007/978-3-642-30284-8_61 fatcat:rafr7otdezfh5bzfxw45qlu7e4

Data-driven solutions for building environmental impact assessment

Qifeng Zhou, Hao Zhou, Yimin Zhu, Tao Li
2015 Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)  
Specifically, first, a feature selection approach is proposed based on the practical demand and construction characteristics to perform assessment analysis.  ...  Second, a unified framework for solving constraint based clustering ensemble selection is proposed to extend the environmental impact assessment range from the building level to the regional level.  ...  Specifically, first, a feature selection approach is proposed based on the practical demand and construction characteristics to perform assessment analysis.  ... 
doi:10.1109/icosc.2015.7050826 dblp:conf/semco/ZhouZZL15 fatcat:wapxjigp4jbyvhvlc72wmvdiba

A study on data mining behavior, challenges and methods

2017 International Journal of Latest Trends in Engineering and Technology  
Various feature selection methods, clustering and classification algorithms are proposed by the researchers to improve the accuracy.  ...  This transformation is also done based on the application and objective of the designed model.  ...  The selected features are processed in a tree form to identify the number of clusters. Later on the algorithmic improvement on basic clustering methods were provided by the researchers.  ... 
doi:10.21172/1.841.40 fatcat:qzq6z3xidreplecgo5mmivkaae

Hepatitis Prediction Model based on Data Mining Algorithm and Optimal Feature Selection to Improve Predictive Accuracy

Varun Kumar.M, Vijaya Sharathi.V, Gayathri Devi.B.R
2012 International Journal of Computer Applications  
Noisy features are identified and eliminated by chi-square attribute evaluation which may further improve the classification accuracy of support vector machine.  ...  Chi-square attribute evaluation is used to assign weight to the attributes thereby improving the classification accuracy.  ...  This method is based upon finding those features which minimize bounds on the leave-one-out error.  ... 
doi:10.5120/8150-1856 fatcat:3nww6y4w2zaszmm3ruusg4ohuq

Text Mining for Protein Docking

Varsha D. Badal, Petras J. Kundrotas, Ilya A. Vakser, Nir Ben-Tal
2015 PLoS Computational Biology  
The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach.  ...  The extracted constraints were incorporated in a modeling procedure, significantly improving its performance. This is a PLOS Computational Biology Methods paper.  ...  Subsets of 50, 40, 30, 20 and 10 features were also selected based on our understanding of importance of a feature for PPI description.  ... 
doi:10.1371/journal.pcbi.1004630 pmid:26650466 pmcid:PMC4674139 fatcat:5usgubv7uzho7iapj4ha26ge7q

Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey

Yalamarthi Leela Sandhya Rani, V. Sucharita, K. V. V. Satyanarayana
2018 International Journal of Electrical and Computer Engineering (IJECE)  
<p class="PreformattedText">Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data.  ...  This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.</p>  ...  It is done with hybrid fuzzy logic feature selection method.  ... 
doi:10.11591/ijece.v8i4.pp2351-2357 fatcat:6khonvlpsreg3h6slnio4jki7m

A Survey on Evolutionary Co-Clustering Formulations for Mining Time-Varying Data Using Sparsity Learning

R.Amsaveni, R. Suresh Kumar
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Two formulations are proposed for evolutionary co-clustering and feature selection based on the fused Lasso regularization.  ...  The data matrix is considered as static in Traditional clustering and feature selection methods. However, the data matrices evolve smoothly over time in many applications.  ...  The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution.  ... 
doi:10.15680/ijircce.2015.0308006 fatcat:zx447bv7erbmlji64eunolhwxy

Multispectral image fusion for detecting land mines

Gregory A. Clark, Sailes K. Sengupta, William D. Aimonetti, Frank Roeske, John G. Donetti, David J. Fields, Robert J. Sherwood, Paul C. Schaich, Abinash C. Dubey, Ivan Cindrich, James M. Ralston, Kelly A. Rigano
1995 Detection Technologies for Mines and Minelike Targets  
Feature Selection :. u. 5.. --- Human experts generally classify objects based on a very few of the most important attributes in the image.  ...  This limits the ability to use features based on shape for object detection. More sophisticated methods that make use of shape information could be used if the camera resolution were greater.  ... 
doi:10.1117/12.211378 fatcat:bxcmuhchmfbbrnj6azwzxxuxl4

Lifting load monitoring of mine hoist through vibration signal analysis with variational mode decomposition

Fan Jiang, Zhencai Zhu, Wei Li, Shixiong Xia, Gongbo Zhou
2017 Journal of Vibroengineering  
To facilitate efficient and accurate monitoring of the lifting load of mine hoist, this paper presents a novel condition-monitoring method based on variational mode decomposition (VMD) and support vector  ...  In this study, experiments on an operated mine hoist are also conducted to verify the reliability and validity of the proposed method.  ...  Based on the above analysis, this study presents a new condition monitoring method, based on EMD, VMD and SVM with vibration signal analysis, to precisely monitor the lifting load of mine hoist.  ... 
doi:10.21595/jve.2017.18859 fatcat:ftrncp3dr5gmtdpicmwsdpmrsq
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