RELARM: A rating model based on relative PCA attributes and k-means clustering

Elnura Irmatova

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arXiv · 1608.06416

RELARM: A rating model based on relative PCA attributes and k-means clustering

Elnura Irmatova

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Abstract

Following widely used in visual recognition concept of relative attributes, the article establishes definition of the relative PCA attributes for a class of objects defined by vectors of their parameters. A new rating model (RELARM) is built using relative PCA attribute ranking functions for rating object description and k-means clustering algorithm. Rating assignment of each rating object to a rating category is derived as a result of cluster centers projection on the specially selected rating vector. Empirical study has shown a high level of approximation to the existing S & P, Moody's and Fitch ratings.

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BibTeX RIS

Elnura Irmatova. 2016-08-23. RELARM: A rating model based on relative PCA attributes and k-means clustering. https://arxiv.org/abs/1608.06416

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