Using MF-ARTMAP neural network for financial data analysis

Title:

Using MF-ARTMAP neural network for financial data analysis

Creator:

Sinčák, Peter, Hric, Marcel, Vaľo, Richard, Horanský, Pavol, and Karel, Pavel

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:1a19b110-639d-4a96-a085-73dc0b1f119e
uuid:1a19b110-639d-4a96-a085-73dc0b1f119e

Subject:

Neural Networks, ART neural networks, fuzzy logic, feature space, classification procedures, fuzzy cluster, fuzzy class, and classification accuracy assessment

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The paper deals with application of MF-ARTMAP neural network on financial fraud data. The focus was on classification of data into 5 types of fraud based on expert knowledge with the aim to achieve the tool with highest classification accuracy. The fraud was characterized by 22 features and the verbal features were encoded into numerical values to be able to use them in the classification proceduře. The results show that in the čase of sufficient data (fraud) representation neural networks could be used with success; in case there are rather small examples, expert generated rules are preferred.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2003 Volume:13 | Number:3

Harvested from:

CDK

Metadata only:

false