Results 91 to 100 of about 3,708,416 (298)
Prediction error: Root mean squared error.
, 2015 Prediction error: Root mean squared error.
Seiya Imoto (115445) +2 more
core +1 more source
Correcting the optimally selected resampling-based error rate: A smooth analytical alternative to nested cross-validation [PDF]
, 2011 High-dimensional binary classification tasks, e.g. the classification of microarray samples into normal and cancer tissues, usually involve a tuning parameter adjusting the complexity of the applied method to the examined data set.
Augustin, Thomas +2 more
core +1 more source
Going viral − Virus‐targeting nanobodies for research, diagnostics and therapy
FEBS Letters, EarlyView.The increasing prevalence of viral diseases represents a major threat for global human health. Nanobodies, small binding fragments derived from camelid heavy‐chain antibodies, offer versatile tools for viral research, diagnostics, and antiviral therapy.
Domenic Ebert, Ulrich Rothbauer
wiley +1 more source
Choosing a Model and Strategy of Model Selection by Accumulated Prediction Error [PDF]
The purpose of the paper is to present and apply the accumulative one-step-ahead prediction error (APE) not only as a method (strategy) of model selection, but also as a tool of model selection strategy (meta-selection).
Mariola Pilatowska
core
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Neuronal Coding of Prediction Errors
Annual Review of Neuroscience, 2000 Associative learning enables animals to anticipate the occurrence of important outcomes. Learning occurs when the actual outcome differs from the predicted outcome, resulting in a prediction error. Neurons in several brain structures appear to code prediction errors in relation to rewards, punishments, external stimuli, and behavioral reactions. In one
Schultz W, Dickinson A
openaire +3 more sources
Reward Prediction Error and Declarative Memory
Trends in Cognitive Sciences, 2020 Learning based on reward prediction error (RPE) was originally proposed in the context of non-declarative memory. We postulate that RPE may support declarative memory as well. Indeed, recent years have witnessed a number of independent empirical studies reporting effects of RPE on declarative memory.
Verguts , Tom +2 more
openaire +4 more sources
Loss of IGF‐1R impairs DNA‐PKcs recruitment to chromatin leading to defective end‐joining
Molecular Oncology, EarlyView.IGF‐1R promotes radioresistance by facilitating DNA‐PKcs recruitment to chromatin, enabling non‐homologous end‐joining (NHEJ) repair of double‐strand breaks. Inhibition or loss of IGF‐1R disrupts this recruitment to damage sites, driving compensatory reliance on microhomology‐mediated end‐joining (MMEJ) repair.
Matthew O. Ellis +3 more
wiley +1 more source
STATISTICAL CHARACTERISTICS INVESTIGATION OF PREDICTION ERRORS FOR INTERFEROMETRIC SIGNAL IN THE ALGORITHM OF NONLINEAR KALMAN FILTERING [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2016 Basic peculiarities of nonlinear Kalman filtering algorithm applied to processing of interferometric signals are considered. Analytical estimates determining statistical characteristics of signal values prediction errors were obtained and analysis of ...
E. L. Dmitrieva, I. P. Gurov
doaj
Risks, 2018 The aim of this paper is to carry out a closed tool to estimate the one-year volatility of the claims reserve, calculated through the generalized linear models (GLM), notably the overdispersed- Poisson model.
Stefano Cavastracci Strascia +1 more
doaj +1 more source