Protein function predictions are usually treated as classification problems where each function is regarded as a class label. However, different from conventional classification problems, they have some specificities that make the classification task more complex. First, the problem classes (protein functions) are usually hierarchically structured, with superclasses and subclasses. Second, prot...

This paper describes a new method for the classification of a HTML document into a hierarchy of categories. The hierarchy of categories is involved in all phases of automated document classification, namely feature extraction, learning, and classification of a new document. The innovative aspects of this work are the feature selection process, the automated threshold determination for classific...

A number of approaches for automatic audio classification are based on hierarchical taxonomies since it is acknowledged that improved performance can be thereby obtained. In this paper, we propose a new strategy to automatically acquire hierarchical taxonomies, using machine learning methods, which are expected to maximize the performance of subsequent classification. It is shown that the optim...

Plant species are living things and are generally categorized in terms of Domain, Kingdom, Phylum, Class, Order, Family, Genus and name of Species in a hierarchical fashion. This paper formulates the taxonomic leaf categorization problem as the hierarchical classification task and provides a suitable solution using a supervised learning technique namely support vector machine. Features are extr...

This projects proposed a hierarchical classification strategy for Amazon products. Classification strategy and the inference efficiency were the two focuses. A strategy to apply general classification algorithms to hierarchical classification problem was proposed. Parallel programing and hashing techniques were applied to improve inference efficiency.

knowledge about spatial soil variation in terms of measured pedodiversity offers the possibility to estimate the quality and variance within a soil map. diversity indices and abundance distribution models are statistical tools which ecologists have applied for decades for analyzing the intrinsic regularities of various ecological entities. in this study relationships between soils evolution, la...

Live fish recognition in the open sea is a challenging multi-class classification task. We propose a hierarchical classification approach to recognize live fish from underwater videos. However, the hierarchical method accumulates misclassified samples into deeper layers and these accumulated errors reduce the average accuracy. We propose a set of heuristics to help construct more accurate hiera...

We study the problem of hierarchical classification when labels corresponding to partial and/or multiple paths in the underlying taxonomy are allowed. We introduce a new hierarchical loss function, the H-loss, implementing the simple intuition that additional mistakes in the subtree of a mistaken class should not be charged for. Based on a probabilistic data model introduced in earlier work, we...

There are various types of classifiers that can be trained on gene expression data with class labels. Many of them have an embedded mechanism for feature selection, by which they distinguish a subset of significant genes that are used for future prediction. When dealing with more than two class labels, especially when the number goes up to a dozen or more, people find it useful to know the rela...

Despite the recent advances in Molecular Biology, the function of a large amount of proteins is still unknown. An approach that can be used in the prediction of a protein function consists of searching against secondary databases, also known as signature databases. Different strategies can be applied to use protein signatures in the prediction of function of proteins. A sophisticated approach c...