Business Plans Classification with Locally Pruned Lazy Learning Models

نویسندگان

  • Antti Sorjamaa
  • Amaury Lendasse
  • Damien Francois
  • Michel Verleysen
چکیده

A business plan is a document presenting in a concise form the key elements describing a perceived business opportunity. It is used among others as a tool for evaluating the feasibility and profitability of a project. In this paper, we study the relationship between business plan quality and venture success. In particular, a classification method using the information from the business plan is used in order to predict the success or the failure of each project. The classification method presented in this paper is based on a linear piecewise approximation method known as Locally Pruned Lazy Learning Model. Key-Words : Lazy Learning, Classification, Leave-one-Out, Pruning Acknowledgements: Part the work of A. Sorjamaa and A. Lendasse is supported by the project New Information Processing Principles, 44886, of the Academy of Finland. The work of D. Francois is supported by a grant from the Belgian FRIA. M. Verleysen is a Senior Research Associate of the Belgian National Fund for Scientific Research. Part of this work is supported by the Interuniversity Attraction Poles (IAP), initiated by the Belgian Federal State, Ministry of Sciences, Technologies and Culture. Dataset has been cordially provided by B. Gailly from UCL, Belgium. ACSEG'2004 proceedings – Connectionist Approaches in Economics and Management Sciences Lille (France), 18-19 November 2004, pp. 112-119

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تاریخ انتشار 2004