RELARM: рейтинговая модель на основе относительных РСА-атрибутов и k-кластеризации

Ирматова Э.А.
RELARM: A rating model based on relative PCA attributes and k-means clustering - View in English

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Аннотация:
В статье, следуя широко используемой в распознавании образов концепции относительных атрибутов, дается определение относительных PCA атрибутов для класса объектов, заданных векторами своих параметров. Построена новая рейтинговая модель, RELARM, использующая ранковые функции относительных PCA атрибутов для описания рейтинговых объектов и алгоритм k-кластеризации. Отнесение каждого рассматриваемого объекта к соответствующей его свойствам рейтинговой категории происходит в результате проецирования центров кластеров на специально выбранный рейтинговый вектор. На тестовой модели кредитоспособности суверенных государств показан высокий уровень аппроксимации рейтингов рейтинговых агентств S&P, Moody’s и Fitch рейтингами RELARM.

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Цитировать публикацию:
Ирматова Э.А. RELARM: рейтинговая модель на основе относительных РСА-атрибутов и k-кластеризации // Российское предпринимательство. – 2017. – Том 18. – № 10. – С. 1597-1614. – doi: 10.18334/rp.18.10.37967

Irmatova, E.A. (2017) RELARM: A rating model based on relative PCA attributes and k-means clustering. Rossiyskoe predprinimatelstvo, 18(10), 1597-1614. doi: 10.18334/rp.18.10.37967 (in Russian)

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