Search results for " Regression"
showing 10 items of 1835 documents
APROXIMACIÓN CONCEPTUAL Y PRÁCTICA A LOS MODELOS DE ECUACIONES ESTRUCTURALES
2017
En el presente trabajo se expone una aproximación conceptual y práctica a los Modelos de Ecuaciones Estructurales o Structural Equation Modeling (SEM). Los SEM están considerados entre las herramientas más potentes para el estudio de relaciones causales en datos no experimentales. Son una combinación del análisis factorial y la regresión múltiple y están compuestos por dos componentes: el modelo de medida y el modelo estructural. El modelo de medida describe la relación existente entre una serie de variables observables; mientras que en el modelo estructural se especifican las relaciones hipotetizadas entre las variables, es decir, se describen las relaciones entre las variables latentes me…
Children and Parental Barriers to Active Commuting to School: A Comparison Study
2021
The main objectives of this study were: to compare the barriers to active commuting to and from school (ACS) between children and their parents separately for children and adolescents; and to analyze the association between ACS and the children’s and parents’ barriers. A total of 401 child–parent pairs, from Granada, Jaén, Toledo and Valencia, self-reported, separately, their mode of commuting to school and work, respectively, and the children’s barriers to ACS. T-tests and chi-square tests were used to analyze the differences by age for continuous and categorical variables, respectively. Binary logistic regressions were performed to study the association between ACS barriers of children an…
L’utilizzo della regressione multipla nelle indagini estimative condotte in mercati fondiari attivi: il caso studio di oliveti e vigneti in un territ…
2012
The present study aims to provide a further contribution to the knowledge about the mechanism of price formation concerning olive orchards and vineyards in a land market of south-west Sicily. Firstly the main characteristics of a sample concerning 42 land properties recently sold in Partanna territory were surveyed and afterwards their relationships between the most relevant among them and the correspondent market prices (both total and unitary sales prices) were investigated through the Multiple Regression Analysis. Finally some propositive remarks were formulated in order to create and successively keep up to date a database of land market prices, necessary tool to improve the quality lev…
Comparison of feature importance measures as explanations for classification models
2021
AbstractExplainable artificial intelligence is an emerging research direction helping the user or developer of machine learning models understand why models behave the way they do. The most popular explanation technique is feature importance. However, there are several different approaches how feature importances are being measured, most notably global and local. In this study we compare different feature importance measures using both linear (logistic regression with L1 penalization) and non-linear (random forest) methods and local interpretable model-agnostic explanations on top of them. These methods are applied to two datasets from the medical domain, the openly available breast cancer …
Machine learning for mortality analysis in patients with COVID-19
2020
This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching…
A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network
2016
International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…
Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data
2022
In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photo…
La rigenerazione del fegato dopo epatectomia: un’analisi mediante regressione multipla del volume futuro residuo epatico mediante l’utilizzo di tomog…
2011
Biomass Assessment of Agricultural Crops Using Multi-temporal Dual-Polarimetric TerraSAR-X Data
2019
The biomass of three agricultural crops, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), was studied using multi-temporal dual-polarimetric TerraSAR-X data. The radar backscattering coefficient sigma nought of the two polarization channels HH and VV was extracted from the satellite images. Subsequently, combinations of HH and VV polarizations were calculated (e.g. HH/VV, HH + VV, HH × VV) to establish relationships between SAR data and the fresh and dry biomass of each crop type using multiple stepwise regression. Additionally, the semi-empirical water cloud model (WCM) was used to account for the effect of crop biomass on radar backscatter …
Authentication of extra virgin olive oils by Fourier-transform infrared spectroscopy
2010
Fourier-transform infrared spectroscopy (FTIR), followed by multivariate treatment of the spectral data, was used to classify vegetable oils according to their botanical origin, and also to establish the composition of binary mixtures of extra virgin olive oil (EVOO) with other low cost edible oils. Oil samples corresponding to five different botanical origins (EVOO, sunflower, corn, soybean and hazelnut) were used. The wavelength scale of the FTIR spectra of the oils was divided in 26 regions. The normalized absorbance peak areas within these regions were used as predictors. Classification of the oil samples according to their botanical origin was achieved by linear discriminant analysis (…