Results 21 to 30 of about 6,412,013 (303)
Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study [PDF]
, 2010 Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the ...
Holder, Roger +12 more
core +2 more sources
Preserving Logical Relations while Estimating Missing Values [PDF]
Revista Română de Statistică, 2017 Item-nonresponse is often treated by means of an imputation technique. In some cases, the data have to satisfy certain constraints, which are frequently referred to as edits.
Ton de Waal, Wieger Coutinho
doaj
A Data-Driven Decision Support System for Scoliosis Prognosis
IEEE Access, 2017 A decision support system with data-driven methods is of great significance for the prognosis of scoliosis. However, developing an accurate and interpretable data-driven decision support system is challenging: 1) the scoliosis data collected from ...
Liming Deng +3 more
doaj +1 more source
A Self-Attention-Based Imputation Technique for Enhancing Tabular Data Quality
Data, 2023 Recently, data-driven decision-making has attracted great interest; this requires high-quality datasets. However, real-world datasets often feature missing values for unknown or intentional reasons, rendering data-driven decision-making inaccurate.
Do-Hoon Lee, Han-joon Kim
doaj +1 more source
Frontotemporal dementia and neuropsychology: the value of missing values [PDF]
Journal of Neurology, Neurosurgery & Psychiatry, 2000 To investigate the effect of missing values due to behavioural disturbances on the neuropsychological test profile in frontotemporal dementia (FTD). The neuropsychological examination of patients with FTD poses a methodological problem. In many patients it is impossible to administer a complete test battery, due to behavioural disturbances inherent to ...
Smeding, H.M.M., Koning, I.
openaire +4 more sources
Mathematical aspects of the kriging applied on landslide in Halenkovice (Czech Republic)
Open Geosciences, 2016 Kriging is one of the geostatistical techniques for spatial data analysis that is usually used for a modelling of natural phenomena or a creation of digital elevation models.
Zůvala Robert +2 more
doaj +1 more source
Data, 2021 It is recognized that the performance of any prediction model is a function of several factors. One of the most significant factors is the adopted preprocessing techniques.
Esra’a Alshdaifat +4 more
doaj +1 more source
Coresets for Clustering with Missing Values
CoRR, 2021 We provide the first coreset for clustering points in $\mathbb{R}^d$ that have multiple missing values (coordinates). Previous coreset constructions only allow one missing coordinate. The challenge in this setting is that objective functions, like $k$-Means, are evaluated only on the set of available (non-missing) coordinates, which varies across ...
Vladimir Braverman +3 more
openaire +4 more sources
Classification of Building Types in Germany: A Data-Driven Modeling Approach
Data, 2022 Details on building levels play an essential part in a number of real-world application models. Energy systems, telecommunications, disaster management, the internet-of-things, health care, and marketing are a few of the many applications that require ...
Abhilash Bandam +4 more
doaj +1 more source
Missing.... presumed at random: cost-analysis of incomplete data [PDF]
, 2002 When collecting patient-level resource use data for statistical analysis, for some patients and in some categories of resource use, the required count will not be observed. Although this problem must arise in most reported economic evaluations containing
Clark, T +15 more
core +1 more source