Combining Multiple Classifiers with Dynamic Weighted Voting

When a multiple classifier system is employed, one of the most popular methods to accomplish the classifier fusion is the simple majority voting. However, when the performance of the ensemble members is not uniform, the efficiency of this type of voting generally results affected negatively. In this paper, new functions for dynamic weighting in classifier fusion are introduced. Experimental results demonstrate the advantages of these novel strategies over the simple voting scheme

Implicitly Constrained Semi-Supervised Least Squares Classification

We introduce a novel semi-supervised version of the least squares classifier. This implicitly constrained least squares (ICLS) classifier minimizes the squared loss on the labeled data among the set of parameters implied by all possible labelings of the unlabeled data. Unlike other discriminative semi-supervised methods, our approach does not introduce explicit additional assumptions into the objective function, but leverages implicit assumptions already present in the choice of the supervised least squares classifier. We show this approach can be formulated as a quadratic programming problem and its solution can be found using a simple gradient descent procedure. We prove that, in a certain way, our method never leads to performance worse than the supervised classifier. Experimental results corroborate this theoretical result in the multidimensional case on benchmark datasets, also in terms of the error rate.Comment: 12 pages, 2 figures, 1 table. The Fourteenth International Symposium on Intelligent Data Analysis (2015), Saint-Etienne, Franc

Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research

Mechanisms of vasomotor sympathetic activity generation in the renovascular hypertension in Wistar rats

The renovascular arterial hypertension (AH) is associated with sympathetic hyperactivity and impaired baroreflex sensitivity determined by increase in circulating angiotensin II (Ang II). The aim of this thesis was to evaluate the role of oxidative stress in the generation and maintenance of the AH (2 Kidney – 1 Clip). Five series of experiments were performed in male Wistar. The results showed autonomic cardiovascular control changes characterized by increased sympathetic modulation in blood vessels, impaired baroreflex sensitivity and tachycardia from the fourth week. Furthermore, we observed that Ang II (via AT-1 receptor) and NO (produced by iNOS) in the rostral ventrolateral medulla (RVLM) are involved in the maintenance of AH and renal sympathetic nerve activity in the 2K-1C. Indeed, there is an imbalance between pro-oxidants and antioxidants in the RVL and hypothalamic paraventricular nucleus (PVN) of animals 2K-1C, because the increase in blood pressure (BP) and sympathetic hyperactivity was reversed in response to administration of the antioxidant (Tempol) into the RVLM and PVN. The over expression of CuZnSOD in the RVLM prevented the AH and reduced the production of superoxide in this region in 2K-1C. Furthermore, improved the impaired baroreflex sensitivity and inhibited the tachycardia observed from the fourth week of AH. Chronic Vitamin C treatment decreased BP and sympathetictactivation in hypertensive animals. In addition, reduced gene expression of subunits of NAD (P) H oxidase in the PVN and RVLM, but unchanged the expression of CuZnSOD. Oxidative stress also seems to influence the gene expression of AT-1 receptor, iNOS, nNOS, IL-1 â and Glut-1 in the PVN and RVL regions, because the treatment reduced the expression of these components. Based on our results, we suggest that the angiotensin system, NO and oxidative stress in the PVN and RVLM are involved in the maintenance of sympathetic tone and the AH 2K-1C. Oxidative stress in sympathetic premotor neurons is a major mechanism for the establishment and maintenance of Ang II – dependent hypertension.A Hipertensão arterial (HA) renovascular está associada com uma hiperatividade simpática e prejuízo na sensibilidade reflexa do barorreceptor determinadas por aumento na Angiotensina II (Ang II) circulante. O objetivo da presente Tese foi avaliar o papel do estresse oxidativo na geração e manutenção da HA 2 Rins-1Clipe. Ratos Machos Wistar foram utilizados em cinco séries de experimentos. Os resultados demonstraram uma alteração no controle autonômico cardíaco caracterizado por maior modulação simpática nos vasos, um prejuízo da sensibilidade reflexa do barorreceptor e taquicardia a partir da quarta semana. Além disso, observou-se que Ang II (via receptor AT-1) e o NO (produzido pela iNOS) na região rostro ventrolateral do bulbo (RVL), participam mantendo a HA e a atividade nervosa simpática renal em ratos 2R-1C. Evidenciou-se um desequilíbrio entre próoxidantes e antioxidantes, caracterizando um estado de estresse oxidativo nas regiões RVL e no núcleo paraventricular (PVN) dos animais 2R-1C, visto que o aumento de pressão arterial (PA) e a hiperatividade simpática são revertidos com a administração do antioxidante (Tempol) nessas regiões. A super expressão crônica de CuZnSOD na região RVL preveniu a HA e reduziu a produção de superóxidos nessa região em ratos 2R-1C. Além disso, melhorou a sensibilidade reflexa do barorreceptor e inibiu a taquicardia observada a partir da quarta semana de HA. O tratamento crônico com Vitamina C promoveu queda da PA e simpato-inibição nos animais hipertensos. Além disso, reduziu a expressão gênica das subunidades de NAD(P)H oxidase nas regiões RVL e PVN, mas não interferiu na expressão de CuZnSOD. O estresse oxidativo também parece influenciar na expressão gênica do receptor AT-1, iNOS, nNOS, IL-1 ƒÀ e Glut-1 nas regioes RVL e PVN, visto que o tratamento reduziu a expressao desses componentes. Baseado em nossos resultados, podemos sugerir que o sistema angiotensinergico, nitrergico e o estresse oxidativo nas regioes RVL e PVN estao envolvidos na manutencao do tonus simpatico e da HA 2R-1C. O estresse oxidativo em neuronios pre-motores do simpatico e um mecanismo essencial para o estabelecimento e manutencao da HA Ang II - dependente.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)FAPESP: 05/60151-6CAPES/BEX: 3496/07-4TEDEBV UNIFESP: Teses e dissertaçõe

Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

<p>Abstract</p> <p>Background</p> <p>Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicine. Derivation of biomarkers is a large step beyond hypothesis generation and imposes considerably more stringency for accuracy in identifying informative gene subsets to differentiate phenotypes. The inherent nature of microarray data, with fewer samples and replicates compared to the large number of genes, requires identifying informative genes prior to classifier construction. However, improving the ability to identify differentiating genes remains a challenge in bioinformatics.</p> <p>Results</p> <p>A new hybrid gene selection approach was investigated and tested with nine publicly available microarray datasets. The new method identifies a Very Important Pool (VIP) of genes from the broad patterns of gene expression data. The method uses a bagging sampling principle, where the re-sampled arrays are used to identify the most informative genes. Frequency of selection is used in a repetitive process to identify the VIP genes. The putative informative genes are selected using two methods, t-statistic and discriminatory analysis. In the t-statistic, the informative genes are identified based on p-values. In the discriminatory analysis, disjoint Principal Component Analyses (PCAs) are conducted for each class of samples, and genes with high discrimination power (DP) are identified. The VIP gene selection approach was compared with the p-value ranking approach. The genes identified by the VIP method but not by the p-value ranking approach are also related to the disease investigated. More importantly, these genes are part of the pathways derived from the common genes shared by both the VIP and p-ranking methods. Moreover, the binary classifiers built from these genes are statistically equivalent to those built from the top 50 p-value ranked genes in distinguishing different types of samples.</p> <p>Conclusion</p> <p>The VIP gene selection approach could identify additional subsets of informative genes that would not always be selected by the p-value ranking method. These genes are likely to be additional true positives since they are a part of pathways identified by the p-value ranking method and expected to be related to the relevant biology. Therefore, these additional genes derived from the VIP method potentially provide valuable biological insights.</p

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

A Tutorial on EEG Signal Processing Techniques for Mental State Recognition in Brain-Computer Interfaces

International audienceThis chapter presents an introductory overview and a tutorial of signal processing techniques that can be used to recognize mental states from electroencephalographic (EEG) signals in Brain-Computer Interfaces. More particularly, this chapter presents how to extract relevant and robust spectral, spatial and temporal information from noisy EEG signals (e.g., Band Power features, spatial filters such as Common Spatial Patterns or xDAWN, etc.), as well as a few classification algorithms (e.g., Linear Discriminant Analysis) used to classify this information into a class of mental state. It also briefly touches on alternative, but currently less used approaches. The overall objective of this chapter is to provide the reader with practical knowledge about how to analyse EEG signals as well as to stress the key points to understand when performing such an analysis