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Title: Effectiveness of active forgetting in machine learning applied to financial problems, Journal of Telecommunications and Information Technology, 2002, nr 3

Creator:

Yoshii, Kengo ; Nakayama, Hirotaka

Date:

2002, nr 3

Resource Type:

artykuł

Description:

One of main features in financial investment problems is that the situation changes very often over time. Under this circumstance, in particular, it has been observed that additional learning plays an effective role. However, since the rule for classification becomes more and more complex with only additional learning, some appropriate forgetting is also necessary. It seems natural that many data are forgotten as the time elapses. On the other hand, it is expected more effective to forget unnecessary data actively. In this paper, several methods for active forgetting are suggested. The effectiveness of active forgetting is shown by examples in stock portfolio problems.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Resource Identifier:

oai:bc.itl.waw.pl:666 ; ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2002.3.137

ISSN:

1509-4553

eISSN:

1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

forgetting additional learning potential method pattern classification

Object collections:

Last modified:

May 28, 2024

In our library since:

Apr 13, 2010

Number of object content hits:

205

All available object's versions:

https://bc.itl.waw.pl/publication/740

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Edition name Date
Nakayama, Hirotaka; Yoshii, Kengo, Effectiveness of active forgetting in machine learning applied to financial problems, Journal of Telecommunications and Information Technology, 2002, nr 3 May 28, 2024

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