We consider multiclass classification problems where the set of labels are organized hierarchically as a category tree. We associate each node in the tree with a classifier and classify the examples recursively from the root to the leaves. We propose a hierarchical Support Vector Machine (SVM) that encourages the classifier at each node to be different from the classifiers at its ancestors. Mor...

Abstract. Accurate and spatially explicit information on forest fuels becomes essential to designing an integrated fire risk management strategy, as fuel characteristics are critical for danger estimation, propagation, emissions modelling, among other aspects. This paper proposes a new European classification system that can be used different spatial scales purposes (propagation, behaviour, emi...

Proteins are the main building blocks of the cell, and perform almost all the functions related to cell activity. Despite the recent advances in Molecular Biology, the function of a large amount of proteins is still unknown. The use of algorithms able to induce classification models is a promising approach for the functional prediction of proteins, whose classes are usually organized hierarchic...

Ant colony optimisation (ACO) is a metaheuristic to solve optimisation problems inspired by the foraging behaviour of ant colonies. It has been successfully applied to several types of optimisation problems, such as scheduling and routing, and more recently for the discovery of classification rules. The classification task in data mining aims at predicting the value of a given goal attribute fo...

In a text categorization task, classification on some hierarchy of classes shows better results than the case without the hierarchy. In current environments where large amount of documents are divided into several subgroups with a hierarchy between them, it is more natural and appropriate to use a hierarchical classification method. We introduce a new internal node evaluation scheme which is ve...

Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This sche...

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published i...

We propose a new method for the morphological galaxy classification which incorporates two main contributions: (i) the generation of artificial images of galaxies through geometric transformations to be used as additional examples in the training phase, (ii) the use of a novel hierarchical classifier for hierarchical galaxy classification. An additional classifier distinguishes galaxies from st...