Results 61 to 70 of about 3,359,701 (313)
Random forest versus logistic regression: a large-scale benchmark experiment
BMC Bioinformatics, 2018 The Random Forest (RF) algorithm for regression and classification has considerably gained popularity since its introduction in 2001. Meanwhile, it has grown to a standard classification approach competing with logistic regression in many innovation ...
R. Couronné +2 more
semanticscholar +1 more source
, 2019 This paper proposes a new classification model called logistic circuits. On MNIST and Fashion datasets, our learning algorithm outperforms neural networks that have an order of magnitude more parameters.
Broeck, Guy Van den, Liang, Yitao
core +1 more source
IEEE AccessStress is a mental health problem that is hazardous if not recognized early. A promising approach for noninvasive stress detection involves leveraging camera technology; however, there are notable challenges involved in this method, particularly ...
Atika Hendryani +2 more
doaj +1 more source
Eterocronia e marginalizzazione di un gruppo di operai siciliani
Cambio, 2018 Through an ethnographic research conducted with a group of Sicilian workers employed in logistics, this paper analyzes the progressive social marginalization of these workers.
Tommaso India
doaj +1 more source
Dynamics of spatial logistic model: finite systems
, 2014 The spatial logistic model is a system of point entities (particles) in $\mathbb{R}^d$ which reproduce themselves at distant points (dispersal) and die, also due to competition.
Kozitsky, Yuri
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Bone tumours present significant challenges for affected patients, as multimodal therapy often leads to prolonged physical limitations. This is particularly critical during childhood and adolescence, as it can negatively impact physiological development and psychosocial resilience.
Jennifer Queisser +5 more
wiley +1 more source
Sample size for binary logistic prediction models: Beyond events per variable criteria
Statistical Methods in Medical Research, 2018 Binary logistic regression is one of the most frequently applied statistical approaches for developing clinical prediction models. Developers of such models often rely on an Events Per Variable criterion (EPV), notably EPV ≥10, to determine the minimal ...
M. van Smeden +6 more
semanticscholar +1 more source
Least-MSE calibration procedures for corrections of measurement and misclassification errors in generalized linear models [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2012 The analyses of clinical and epidemiologic studies are often based on some kind of regression analysis, mainly linearregression and logistic models. These analyses are often affected by the fact that one or more of the predictors are measuredwith error ...
Parnchit Wattanasaruch +2 more
doaj
Real‐time assay of ribonucleotide reductase activity with a fluorescent RNA aptamer
FEBS Letters, EarlyView.Ribonucleotide reductases (RNR) synthesize DNA building blocks de novo, making them crucial in DNA replication and drug targeting. FLARE introduces the first single‐tube real‐time coupled RNR assay, which enables isothermal tracking of RNR activity at nanomolar enzyme levels and allows the reconstruction of allosteric regulatory patterns and rapid ...
Jacopo De Capitani +4 more
wiley +1 more source
Malaysian Journal of Medical Sciences, 2018 Background Different study designs and population size may require different sample size for logistic regression. This study aims to propose sample size guidelines for logistic regression based on observational studies with large population.
M. Bujang +3 more
semanticscholar +1 more source