WIT Press


Detecting Visual Feature Importance Via Tree Classifiers. An Experience

Price

Free (open access)

Paper DOI

10.2495/DATA000471

Volume

25

Pages

7

Published

2000

Size

775 kb

Author(s)

C. Brambilla, I. Gagliardi, R. Schettini & A. Valsasna

Abstract

In this work we present an experience of using tree classifiers as a tool of multivari- ate exploratory analysis. It refers to a problem of image analysis, and specifically to that of identifying low-level visual features suitable to capture salient aspects of the semantic content of the images. The problem is addressed by studying the discrimination capability of the features towards classes of images semantically defined. The classes considered are the photograph, graphic and text classes. 1 Introduction In multivariate problems, in response to the increasing dimensionality of the data, there is an increasing need of methods of analysis able to detect redundancy and select relevant variables. Aim of the present work is to ill

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