Search results for " regression"
showing 10 items of 1835 documents
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Nonlinear statistical retrieval of surface emissivity from IASI data
2017
Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…
Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy)
2016
Debris flows are among the most hazardous phenomena in nature, requiring the preparation of suscep- tibility models in order to cope with this severe threat. The aim of this research was to verify whether a grid cell-based susceptibility model was capable of predicting the debris- flow initiation sites in the Giampilieri catchment (10 km2), which was hit by a storm on the 1st October 2009, resulting in more than one thousand landslides. This kind of event is to be considered as recurrent in the area as attested by historical data. Therefore, predictive models have been prepared by using forward stepwise binary logistic regression (BLR), a landslide inventory and a set of geo- environmental …
The regression Tsetlin machine: a novel approach to interpretable nonlinear regression
2019
Relying simply on bitwise operators, the recently introduced Tsetlin machine (TM) has provided competitive pattern classification accuracy in several benchmarks, including text understanding. In this paper, we introduce the regression Tsetlin machine (RTM), a new class of TMs designed for continuous input and output, targeting nonlinear regression problems. In all brevity, we convert continuous input into a binary representation based on thresholding, and transform the propositional formula formed by the TM into an aggregated continuous output. Our empirical comparison of the RTM with state-of-the-art regression techniques reveals either superior or on par performance on five datasets. Thi…
Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a…
2017
Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils and beans), spot urine samples from a subcohort from the PREDIMED study were stratified, using a validated food frequency questionnaire. Non-pulse consumers (≤ 4 g/day of pulse intake) and habitual pulse consumers (≥ 25 g/day of pulse intake) were analysed using a 1H-NMR metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through…
Association between parental feeding practices and shared family meals. The Food4toddlers study
2020
Background Parental feeding practices and family meals are important determinants for infants' diet and health. Still, there is no previous research of the association between feeding practices and family meals in infants. Objective Explore potential associations between feeding practices and family meals among infants. Design We present cross-sectional results (baseline) from the Food4toddlers study. In total 298 parents of 1-year-olds, recruited from all over Norway, filled in a questionnaire regarding frequency of shared family meals (breakfast, lunch, dinner) and feeding practices using the validated instrument Comprehensive Feeding Practices Questionnaire. Logistic regression was used …
Sex- and age patterns in incidence of infectious diseases in Germany: analyses of surveillance records over a 13-year period (2001–2013)
2018
AbstractSex differences in the incidence of infections may indicate different risk factors and behaviour but have not been analysed across pathogens. Based on 3.96 million records of 33 pathogens in Germany, notified from 2001 to 2013, we applied Poisson regression to generate age-standardised incidence rate ratios and assessed their distribution across age and sex. The following trends became apparent: (a) pathogens with male incidence preponderance at infant and child age (meningococcal disease (incidence rate ratio (IRR) = 1.19, 95% CI 1.03–1.38, age = 0–4); influenza (IRR = 1.09, 95% CI 1.06–1.13, age = 0–4)), (b) pathogens with sex-switch in incidence preponderance at puberty (e.g. nor…
Examining the "Veggie" personality: Results from a representative German sample.
2017
Abstract An increasing proportion of people choose to follow a vegetarian diet. To date, however, little is known about if and how individual differences in personality relate to following a vegetarian diet. In the two studies presented here, we aimed to (1) estimate the prevalence of self-defined vegetarians in two waves of a German representative sample (N = 4496 and 5125, respectively), (2) analyze the effect of socio-demographic variables on dietary behavior, and (3) examine individual differences between vegetarians and meat eaters in personality traits, political attitudes, and health-related variables. In Study 1, a strict definition of vegetarians was used, while in Study 2 the defi…
Temporal association between the influenza virus and respiratory syncytial virus (RSV): RSV as a predictor of seasonal influenza.
2016
SUMMARYEpidemiologists agree that there is a prevailing seasonality in the presentation of epidemic waves of respiratory syncytial virus (RSV) infections and influenza. The aim of this study is to quantify the potential relationship between the activity of RSV, with respect to the influenza virus, in order to use the RSV seasonal curve as a predictor of the evolution of an influenza virus epidemic wave. Two statistical tools, logistic regression and time series, are used for predicting the evolution of influenza. Both logistic models and time series of influenza consider RSV information from previous weeks. Data consist of influenza and confirmed RSV cases reported in Comunitat Valenciana (…
Ocrelizumab Extended Interval Dosing in Multiple Sclerosis in Times of COVID-19.
2021
ObjectiveTo evaluate the clinical consequences of extended interval dosing (EID) of ocrelizumab in relapsing-remitting multiple sclerosis (RRMS) during the coronavirus disease 2019 (COVID-19) pandemic.MethodsIn our retrospective, multicenter cohort study, we compared patients with RRMS on EID (defined as ≥4-week delay of dose interval) with a control group on standard interval dosing (SID) at the same period (January to December 2020).ResultsThree hundred eighteen patients with RRMS were longitudinally evaluated in 5 German centers. One hundred sixteen patients received ocrelizumab on EID (median delay [interquartile range 8.68 [5.09–13.07] weeks). Three months after the last ocrelizumab in…