Search results for " Regression"
showing 10 items of 1835 documents
Association between Anxiety, Quality of Life and Academic Performance of the Final-Year-Students in Latvia
2021
The main objective of this study was to investigate the association between final-year students’ anxiety level and quality of life (QOL) with their academic achievements. A longitudinal study was performed in regular schools and in high-rated gymnasiums at the beginning and at the end of the school year. Multiple linear regression models were built for the association between level of anxiety/QOL with academic achievements. Type of school and gender—but not the level of anxiety—were the main predictors of academic achievements of 287 adolescents (e.g., for mathematics, the effect estimates were: β = −1.71 [95% confidence interval −2.21
Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction
2015
Gaussian Process Regression (GPR) for machine learning has lately been successfully introduced for chlorophyll content mapping from remotely sensed data. The method provides a fast, stable and accurate prediction of biophysical parameters. However, since GPR is a non-linear kernel regression method, the relevance of the features are not accessible. In this paper, we introduce a probabilistic approach for feature sensitivity analysis (SA) of the GPR in order to reveal the relative importance of the features (bands) being used in the regression process. We evaluated the SA on GPR ocean chlorophyll content prediction. The method revealed the importance of the spectral bands, thus allowing the …
Exploiting ongoing EEG with multilinear partial least squares during free-listening to music
2016
During real-world experiences, determining the stimulus-relevant brain activity is excitingly attractive and is very challenging, particularly in electroencephalography. Here, spectrograms of ongoing electroencephalogram (EEG) of one participant constructed a third-order tensor with three factors of time, frequency and space; and the stimulus data consisting of acoustical features derived from the naturalistic and continuous music formulated a matrix with two factors of time and the number of features. Thus, the multilinear partial least squares (PLS) conforming to the canonical polyadic (CP) model was performed on the tensor and the matrix for decomposing the ongoing EEG. Consequently, we …
How news affect the trading behavior of different categories of investors in a financial market
2015
We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the exogenous factors we use are the total daily number of news and a semantic variable based on a sentiment analysis of news. Linear regression and partial correlation analysis of data show that different categories of investors are differently correlated to these factors. Governmental and non profit organizations are weakly sensitive to news and returns or volatility, and, typica…
Perceived Opportunities for Physical Activity and Willingness to Be More Active in Older Adults with Different Physical Activity Levels
2021
This study examined equity in physical activity (PA) by investigating whether perceived opportunity for PA was associated with willingness to be more active. Among community residents (75, 80, or 85 years old, n = 962) perceived opportunity for PA (poor and good), willingness to be more active (not at all, a bit, and a lot), and level of PA (low, moderate, and high) were assessed via questionnaires. Multinomial logistic regression showed that physical activity moderated the association between poor opportunity and willingness to increase PA. Among those with moderate PA, poor opportunity for PA increased the odds of willingness to be a lot more active (multinomial odds ratio, mOR 3.90, 95% …
Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression
2020
Multi-target regression is a special subset of supervised machine learning problems. Problem transformation methods are used in the field to improve the performance of basic methods. The purpose of this article is to test the use of recently popularized distance-based methods, the minimal learning machine (MLM) and the extreme minimal learning machine (EMLM), in problem transformation. The main advantage of the full data variants of these methods is the lack of any meta-parameter. The experimental results for the MLM and EMLM show promising potential, emphasizing the utility of the problem transformation especially with the EMLM. peerReviewed
High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di D…
2018
[EN] The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and …
Estimating traffic operations at multi-lane roundabouts: A case study
2014
This paper addresses traffic modeling issues at urban multi-lane roundabouts where, despite circulating vehicles have priority, negotiation of the right-of-way can occur between antagonist traffic flows, as a result of minor drivers’ failing to obey the nominal operating rule (stop or yield control). Existing models for the estimation of operational performances have the shortcoming of not representing the interdependencies between entering and circulating vehicles at multi-lane roundabouts. An analytical capacity model derived from field observations was developed for this kind of intersections in a previous study. The complexity of the model lies in the difficulty of observing the behavio…
Active commuting to school among 36,781 Spanish children and adolescents: A temporal trend study.
2021
This study examines trends in the rates of active commuting to school (ACS) in Spanish children (n = 18 343; 8.93 ± 1.68) and adolescents (n = 18 438; 14.11 ± 1.58) aged 6‐18 years from 2010 to 2017. Given the study period included the economic crisis in Spain (2008‐2013), the second aim of this study was to compare ACS rates during and after the economic crisis. Data were obtained from 28 studies conducted across Spain. The overall trends in ACS were evaluated using multilevel logistic regression analysis. Among Spanish children and adolescents, the rates of ACS to school ranged around 60% between 2010 and 2017. The rates of ACS in Spanish youth did not change significantly during the 2010…
The Effects of Consumer Demographics and Payment Method Preference on Product Return Frequency and Reasons in Online Shopping
2021
In online shopping, product returns are very common. In order to reduce them, one must first understand who are making them and why are they being made. In this study, we aim to address these questions by examining product return behaviour from a consumer-centric rather than the more traditional product-centric, retailer-centric, and order-centric perspectives. More specifically, we focus on the effects of four demographic characteristics of consumers (i.e., gender, age, education, and income) as well as their payment method preference on their product return frequency and product return reasons. As the data, we use the responses from 560 Finnish online consumers, which were collected with …