A systematic comparison of supervised classifiers

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration

Strangeness, Charm and Beauty in Quark Matter: SQM 2007 Experimental Overview

This paper aims at providing an experimental overview of the Strangeness in Quark Matter 2007 ConferenceComment: Proceedings of Strangeness in Quark Matter 2007, submitted to Journal of Physics

Molecular diversity within the genus Laeonereis (Annelida, Nereididae) along the west Atlantic coast: paving the way for integrative taxonomy

The polychaete genus Laeonereis (Annelida, Nereididae) occurs over a broad geographic range and extends nearly across the entire Atlantic coast of America, from the USA to Uruguay. Despite the research efforts to clarify its diversity and systematics, mostly by morphological and ecological evidence, there is still uncertainty, mainly concerning the species Laeonereis culveri, which constitutes an old and notorious case of taxonomic ambiguity. Here, we revised the molecular diversity and distribution of Laeonereis species based on a multi-locus approach, including DNA sequence analyses of partial segments of the cytochrome c oxidase subunit I (COI), 16S rRNA, and 28S rRNA genes. We examined Laeonereis specimens collected from 26 sites along the American Atlantic coast from Massachusetts (USA) to Mar del Plata (Argentina). Although no comprehensive morphological examination was performed between different populations, the COI barcodes revealed seven highly divergent MOTUs, with a mean K2P genetic distance of 16.9% (from 6.8% to 21.9%), which was confirmed through four clustering algorithms. All MOTUs were geographically segregated, except for MOTUs 6 and 7 from southeastern Brazil, which presented partially overlapping ranges between Rio de Janeiro and Sao Paulo coast. Sequence data obtained from 16S rRNA and 28S rRNA markers supported the same MOTU delimitation and geographic segregation as those of COI, providing further evidence for the existence of seven deeply divergent lineages within the genus. The extent of genetic divergence between MOTUs observed in our study fits comfortably within the range reported for species of polychaetes, including Nereididae, thus providing a strong indication that they might constitute separate species. These results may therefore pave the way for integrative taxonomic studies, aiming to clarify the taxonomic status of the Laeonereis MOTUs herein reported.This work was supported by the FAPESP (Grants n~ 2011/50317-5, 2015/25623-6, 2017/06167-5, 2018/10313-0) and CNPq through a productivity grant to A.C.Z.A (301551/2019-7). Marcos AL Teixeira was supported by a PhD fellowship (SFRH/BD/131527/2017) from FCT. Pedro Vieira was supported by a Post-Doctoral Fellowships (BPD1/next-sea/2018, NORTE-01-0145-FEDER-000032). Filipe Costa and the University of Minho's contribution was supported by the strategic program UID/BIA/04050/2013 POCI-010145-FEDER-007569. Victor C Seixas was supported by a Post-Doctoral Fellowship sponsored by CAPES-PNPD (88882.316714/2019-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Methods to convert continuous outcomes into odds ratios of treatment response and numbers needed to treat: meta-epidemiological study

Background Clinicians find standardized mean differences (SMDs) calculated from continuous outcomes difficult to interpret. Our objective was to determine the performance of methods in converting SMDs or means to odds ratios of treatment response and numbers needed to treat (NNTs) as more intuitive measures of treatment effect. Methods Meta-epidemiological study of large-scale trials (≥100 patients per group) comparing active treatment with placebo, sham or non-intervention control. Trials had to use pain or global symptoms as continuous outcomes and report both the percentage of patients with treatment response and mean pain or symptom scores per group. For each trial, we calculated odds ratios of observed treatment response and NNTs and approximated these estimates from SMDs or means using all five currently available conversion methods by Hasselblad and Hedges (HH), Cox and Snell (CS), Furukawa (FU), Suissa (SU) and Kraemer and Kupfer (KK). We compared observed and approximated values within trials by deriving pooled ratios of odds ratios (RORs) and differences in NNTs. ROR <1 and positive differences in NNTs imply that approximations are more conservative than estimates calculated from observed treatment response. As measures of agreement, we calculated intraclass correlation coefficients. Results A total of 29 trials in 13 654 patients were included. Four out of five methods were suitable (HH, CS, FU, SU), with RORs between 0.92 for SU [95% confidence interval (95% CI), 0.86-0.99] and 0.97 for HH (95% CI, 0.91-1.04) and differences in NNTs between 0.5 (95% CI, −0.1 to −1.6) and 1.3 (95% CI, 0.4-2.1). Intraclass correlation coefficients were ≥0.90 for these four methods, but ≤0.76 for the fifth method by KK (P for differences ≤0.027). Conclusions The methods by HH, CS, FU and SU are suitable to convert summary treatment effects calculated from continuous outcomes into odds ratios of treatment response and NNTs, whereas the method by KK is unsuitabl