ELM Clustering – Application to Bankruptcy Prediction

Anton Akusok; David Veganzones; Kaj-Mikael Björk; Eric Séverin; Philippe du Jardin; Amaury Lendasse; Yoan Miche

ELM Clustering – Application to Bankruptcy Prediction

Anton Akusok, David Veganzones, Kaj-Mikael Björk, Eric Séverin, Philippe du Jardin, Amaury Lendasse, Yoan Miche

Finansiell ekonomi, Helsingfors

Arcada University of Applied Sciences

Forskningsoutput: Kapitel i bok/rapport/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

Sammanfattning

This paper presents a new clustering technique based on Ex-treme Learning Machine (ELM). This clustering technique can incorpo-rate a priori knowledge (of an expert) to define the optimal structure of the clustering; for example, the number of points in each cluster. Using ELM, the clustering can be rewritten as a Traveling Salesman Problem and solved by a Genetic Algorithm. This efficient and fast clustering technique is used in order to analyze and predict financial distress of French companies.

Originalspråk	Engelska
Titel på värdpublikation	International work-conference on Time Series (ITISE)
Utgivningsdatum	2014
Status	Publicerad - 2014
MoE-publikationstyp	A4 Artikel i en konferenspublikation

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512 Företagsekonomi

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@inproceedings{e66093d1296f42098cd07e29f536d90b,

title = "ELM Clustering – Application to Bankruptcy Prediction",

abstract = "This paper presents a new clustering technique based on Ex-treme Learning Machine (ELM). This clustering technique can incorpo-rate a priori knowledge (of an expert) to define the optimal structure of the clustering; for example, the number of points in each cluster. Using ELM, the clustering can be rewritten as a Traveling Salesman Problem and solved by a Genetic Algorithm. This efficient and fast clustering technique is used in order to analyze and predict financial distress of French companies. ",

keywords = "512 Business and Management",

author = "Anton Akusok and David Veganzones and Kaj-Mikael Bj{\"o}rk and Eric S{\'e}verin and {du Jardin}, Philippe and Amaury Lendasse and Yoan Miche",

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T1 - ELM Clustering – Application to Bankruptcy Prediction

AU - Akusok, Anton

AU - Veganzones, David

AU - Björk, Kaj-Mikael

AU - Séverin, Eric

AU - du Jardin, Philippe

AU - Lendasse, Amaury

AU - Miche, Yoan

PY - 2014

Y1 - 2014

N2 - This paper presents a new clustering technique based on Ex-treme Learning Machine (ELM). This clustering technique can incorpo-rate a priori knowledge (of an expert) to define the optimal structure of the clustering; for example, the number of points in each cluster. Using ELM, the clustering can be rewritten as a Traveling Salesman Problem and solved by a Genetic Algorithm. This efficient and fast clustering technique is used in order to analyze and predict financial distress of French companies.

AB - This paper presents a new clustering technique based on Ex-treme Learning Machine (ELM). This clustering technique can incorpo-rate a priori knowledge (of an expert) to define the optimal structure of the clustering; for example, the number of points in each cluster. Using ELM, the clustering can be rewritten as a Traveling Salesman Problem and solved by a Genetic Algorithm. This efficient and fast clustering technique is used in order to analyze and predict financial distress of French companies.

KW - 512 Business and Management

M3 - Conference contribution

BT - International work-conference on Time Series (ITISE)

ER -

ELM Clustering – Application to Bankruptcy Prediction

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