In this paper, we present a series of experiments on the automated classification of Cassin’s Vireo individuals from song phrases using support vector machines and from sequences of song phrases using hidden Markov models. Experimental results show that accurate classification of bird individuals can be achieved using these two different levels of description of bird songs.

In this paper we present a combined SVM-HMM sleep spindle detection scheme. The proposed scheme takes advantage of the information provided from each of the two prediction models in decision level, in order to provide refined and more accurate spindle detection results. The experimental results showed that the proposed combined scheme achieved an overall detection performance of 90.28%, increas...

Informatics around public health are increasingly shifting from the professional to the public spheres. In this work, we apply linguistic analytics to restaurant reviews, from Yelp, in order to automatically predict official health inspection reports. We consider two types of feature sets, i.e., keyword detection and topic model features, and use these in several classification methods. Our emp...

Protein-protein interactions play essential roles in protein function implementation. A computational model is introduced in this work for predicting protein interface residues based on amino acid chemicophysical properties only. 17 amino acid properties are selected from AAindex database and used as input features of a prediction model which is constructed by support vector machines method to ...

This study’s aim is to predict speaker personality from intonation patterns in spoken dialogs. Intonation patterns were extracted by a parametric superpositional stylization approach that allows for pattern description on a parametric as well as on a categorical level. Based on features derived from these representations we trained support vector machines and fitted generalized linear regressio...

In this paper we address the problem of classifying handwritten data with respect to gender and handedness. For the classification we apply state-of-the-art classification methods to distinguish between male and female handwriting, and leftand righthandedness. Two classification systems have been evaluated, the first being based on Support Vector Machines and the second being based on Gaussian ...

Deciding whether borrowers can fulfill their obligations is a major issue for financial institutions, and while various credit rating models have been developed to help achieve this, they cannot reflect the domain knowledge of human experts. This paper proposes a new rating model based on a support vector machine with monotonicity constraints derived from the prior knowledge of financial expert...

We describe a method for solving large-scale semiparametric support vector machines (SVMs) for regression problems. Most of the approaches proposed to date for large-scale SVMs cannot accommodate the multiple equality constraints that appear in semiparametric problems. Our approach uses a decomposition framework, with a primal-dual algorithm to find an approximate saddle point for the min-max f...

automatic facial recognition has many potential applications in different areas of humancomputer interaction. however, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. in this paper, we present a new appearance based feature descriptor,the local directional pattern (ldp), to represent facial geometry and analyze its performance inrecognition. an ldp feat...

we can reach by dna microarray gene expression to such wealth of information with thousands of variables (genes). analysis of this information can show genetic reasons of disease and tumor differences. in this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...