Advanced search ?

Object

Download

Title: Solving Support Vector Machine with Many Examples, Journal of Telecommunications and Information Technology, 2010, nr 3

Autor:

Białoń, Paweł

Data wydania:

2010, nr 3

Typ zasobu:

artykuł

Opis:

Various methods of dealing with linear support vector machine (SVM) problems with a large number of examples are presented and compared. The author believes that some interesting conclusions from this critical analysis applies to many new optimization problems and indicates in which direction the science of optimization will branch in the future. This direction is driven by the automatic collection of large data to be analyzed, and is most visible in telecommunications. A stream SVM approach is proposed, in which the data substantially exceeds the available fast random access memory (RAM) due to a large number of examples. Formally, the use of RAM is constant in the number of examples (though usually it depends on the dimensionality of the examples space). It builds an inexact polynomial model of the problem. Another author’s approach is exact. It also uses a constant amount of RAM but also auxiliary disk files, that can be long but are smartly accessed. This approach bases on the cutting plane method, similarly as Joachims’ method (which, however, relies on early finishing the optimization).

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Identyfikator zasobu:

oai:bc.itl.waw.pl:1057 ; ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2010.3.1086

ISSN:

1509-4553

eISSN:

1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

data mining network failure detection concept drift stream processing support vector machines convex optimization

Object collections:

Last modified:

28 sie 2024

In our library since:

13 mar 2012

Number of object content hits:

130

All available object's versions:

https://ribes-54.man.poznan.pl/publication/1175

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Białoń, Paweł, Solving Support Vector Machine with Many Examples, Journal of Telecommunications and Information Technology, 2010, nr 3 28 sie 2024

Objects Similar
An Online Stream Monitoring Algorithm for Fraud Detection in the Transport of Goods, Journal of Telecommunications and Information Technology, 2020, nr 4

Białoń, Paweł M.

2020, nr 4
artykuł
2023, nr 4, JTIT-artykuły
2023, nr 4, JTIT-artykuły
A Problem of Detecting Stops While Tracking Moving Objects Under the Stream Processing Regime, Journal of Telecommunications and Information Technology, 2023, nr 4

Białoń, Paweł

2023
artykuł
Event mining based on observations of the system, Journal of Telecommunications and Information Technology, 2005, nr 3

Granat, Janusz

2005, nr 3
artykuł
A framework for event based modeling and analysis, Journal of Telecommunications and Information Technology, 2006, nr 4

Granat, Janusz

2006, nr 4
artykuł
Modeling preparation for data mining processes, Journal of Telecommunications and Information Technology, 2006, nr 4

Euler, Timm

2006, nr 4
artykuł
Modified PSO Based Channel Allocation Scheme for Interference Management in 5G Wireless Mesh Networks, Journal of Telecommunications and Information Technology, 2022, nr 2

Manvi, Sunilkumar S. Benni, Nirmalkumar S.

2022, nr 2
artykuł
Briefly on the GUHA method of data mining, Journal of Telecommunications and Information Technology, 2003, nr 3

Hajek, Petr

2003, nr 3
artykuł
A Novel System Architecture for an Improved Self-care Solution – Conceptual Design and Key Components, Journal of Telecommunications and Information Technology, 2020, nr 4

Ramos, Jorge Seabra, Eduardo Castro, José Santos, Patrick

2020, nr 4
artykuł
More
×

Citation

Citation style:

Contact details

Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

Visit us!

This page uses 'cookies'. More information