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Añadir al carritoPaperback or Softback. Condición: New. A study on network intrusion detection using classifiers. Book.
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Publicado por Editions Notre Savoir, 2025
ISBN 10: 6209319777 ISBN 13: 9786209319778
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Publicado por LAP LAMBERT Academic Publishing, 2017
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (undergraduate) from the year 2019 in the subject Computer Science - Applied, VIT University, language: English, abstract: In these days of rising internet usage, almost everyone has access to the internet. It is available easily and readily. So along with increase in popularity and importance it also leads to an increase in risks and susceptibility to unwanted attacks. Networks and servers and more prone to malicious attacks than ever. Cyber security is vital in this age. Lots of organizations now interact and communicate with people via the internet. They store huge amounts of data in their computers or devices connected to the network. This data should only be accessed by authorized members of the organization. It is possible for hackers to gain unauthorized access to this data. A lot of sensitive information is present in the data which might lead to harm in the hands of hackers. It is important to protect the network from being attacked in such a way. Network security is an element of cyber security which aims to provide services so that the organizations are safe from such attacks. Intrusion detection systems are present in the network which work along with the firewalls to detect and prevent such attacks. For this project, we aim to identify the suitable machine learning technique to detect such attacks and which can be used in state of the art system.
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Scientific Essay from the year 2017 in the subject Computer Science - Bioinformatics, grade: 3, , language: English, abstract: This survey aims to analyze a large number of existing methods to biclustering, and classify them in accordance with the methods used to perform the search.DNA microarray aims at extracting useful information that can be applied in medical and biological studies. Clustering is one of the most utilized data mining technique to analyze the gene expression data. Generally, there are subsets of genes that behave similarily or under subsets of conditions. Therefore, biclustering is introduced to identify the subgroups of genes and subgroups of conditions by performing simultaneous clustering of both rows and columns of the gene expression matrix, rather than clustering these two dimensions separately. DNA microarray technologies have made it feasible to monitor transcription levels of tens of thousands of genes in a single expriement. A typical DNA microarray experiment involves a multistep procedure: fabrication of microarrays by fixing properly designed oligonucleotides representing specific genes; hybridization of cDNA populations onto the microarray; scanning hybridization signals and image analysis; transformation and normalization of data; and analyzing data to identify differentially expressed genes as well as sets of genes that are co-regulated.
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (undergraduate) from the year 2015 in the subject Computer Science - Bioinformatics, grade: 1, Bannari Amman Institute of Technology, language: English, abstract: Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data. If two different genes show similar expression patterns across the samples, this suggests a common pattern of regulation or relationship between their functions. These patterns have huge significance and application in bioinformatics and clinical research such as drug discovery, treatment planning, accurate diagnosis, prognosis, protein network analysis and so on.In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced. Clustering is a global model where as biclustering is a local model. Discovering such local expression patterns is essential for identifying many genetic pathways that are not apparent otherwise. It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.Biclustering is a two dimensional clustering problem where we group the genes and samples simultaneously. It has a great potential in detecting marker genes that are associated with certain tissues or diseases. However, since the problem is NP-hard, there has been a lot of research in biclustering involving statistical and graph-theoretic. The proposed Cuckoo Search (CS) method finds the significant biclusters in large expression data. The experiment results are demonstrated on benchmark datasets. Also, this work determines the biological relevance of the biclusters with Gene Ontology in terms of function.
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Añadir al carritoTaschenbuch. Condición: Neu. A study on network intrusion detection using classifiers | Balamurugan Rengeswaran | Taschenbuch | 44 S. | Englisch | 2019 | GRIN Verlag | EAN 9783346039132 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. A Nature Inspired Algorithm for Biclustering Microarray Data Analysis | B. Rengeswaran (u. a.) | Taschenbuch | 48 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668619531 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202024259 ISBN 13: 9786202024259
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. An Approach for Market Segmentation using Customer Pain Points | Balamurugan Rengeswaran | Taschenbuch | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202024259 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659746398 ISBN 13: 9783659746390
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Añadir al carritoTaschenbuch. Condición: Neu. Biclustering of Microarray Gene Expression Data : | With Heuristic Approach | Balamurugan Rengeswaran (u. a.) | Taschenbuch | 56 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659746390 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139457807 ISBN 13: 9786139457809
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Añadir al carritoTaschenbuch. Condición: Neu. Parallelization in Traditional Clustering Algorithms | Balamurugan Rengeswaran | Taschenbuch | 52 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139457809 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Idioma: Español
Publicado por Ediciones Nuestro Conocimiento, 2022
ISBN 10: 6204501356 ISBN 13: 9786204501352
Librería: moluna, Greven, Alemania
EUR 34,25
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Idioma: Francés
Publicado por Editions Notre Savoir, 2025
ISBN 10: 6209319777 ISBN 13: 9786209319778
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139457807 ISBN 13: 9786139457809
Librería: Buchpark, Trebbin, Alemania
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 52 | Sprache: Englisch | Produktart: Bücher | Clustering is one of the ways to classify and segregate data into clusters or groups based on the similarity between them. But this process can be a very time consuming task. The goal is to reduce the time taken for computation and keep the performance of the algorithm consistent. To achieve this, we parallelize the algorithm such that various independent segments can run concurrently and hence reduce the execution time while giving the same performance.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139457807 ISBN 13: 9786139457809
Librería: Buchpark, Trebbin, Alemania
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Seiten: 52 | Sprache: Englisch | Produktart: Bücher | Clustering is one of the ways to classify and segregate data into clusters or groups based on the similarity between them. But this process can be a very time consuming task. The goal is to reduce the time taken for computation and keep the performance of the algorithm consistent. To achieve this, we parallelize the algorithm such that various independent segments can run concurrently and hence reduce the execution time while giving the same performance.