Results 61 to 70 of about 6,412,013 (303)
Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation [PDF]
, 2008 Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can tolerate missing values, namely C4.5, to predict cost using six real world
Liu, J, Song, Q, Shepperd, MJ, Chen, X
core +1 more source
An RNN-Based Delay-Guaranteed Monitoring Framework in Underwater Wireless Sensor Networks
IEEE Access, 2019 Real-time underwater monitoring has been widely applied in many applications of underwater wireless sensor networks (UWSNs). Due to the long acoustic communication delays, the real-time data collection in UWSNs is challenging.
Xiaohui Wei +4 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cytomegalovirus (CMV) is a recognized trigger of immune thrombocytopenia (ITP); however, its incidence and impact on disease course in children remain controversial. Therefore, we aimed to characterize the clinical course of pediatric patients with CMV‐associated ITP.
Oded Gilad +9 more
wiley +1 more source
Missing Value Imputation with Unsupervised Backpropagation [PDF]
Computational Intelligence, 2014 AbstractMany data mining and data analysis techniques operate on dense matrices or complete tables of data. Real‐world data sets, however, often contain unknown values. Even many classification algorithms that are designed to operate with missing values still exhibit deteriorated accuracy.
Michael S. Gashler +3 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Reduced bone mineral density (BMD) has been reported in survivors of childhood and young adult acute lymphoblastic leukaemia (ALL); however, data from cohorts treated with contemporary protocols and including matched controls remain limited.
Karen Schow Jensen +10 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Standards for Psychosocial Care for Children with Cancer and Their Families guide the provision of comprehensive psychosocial care. Parallel to research characterizing implementation of the Standards from the perspective of providers, this study examines implementation of the Standards from the perspective of parents of youth ...
Emily M. Pariseau +8 more
wiley +1 more source
The Hidden Value of Missing Genotypes [PDF]
Molecular Biology and Evolution, 2006 Robotic systems allow vast genetic data sets to be generated automatically with little manual input, raising questions about accuracy. To test whether errors occur randomly, I used the frequencies of missing genotypes in a large human data set to construct a population tree.
openaire +2 more sources
Spectrum Occupancy Reconstruction in Distributed Cognitive Radio Networks Using Deep Learning
IEEE Access, 2019 Spectrum occupancy reconstruction is an important issue often encountered in collaborative spectrum sensing in distributed cognitive radio networks (CRNs).
Mduduzi C. Hlophe, Sunil B. T. Maharaj
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric intramedullary low‐grade gliomas (PIMLGGs) are rare neoplasms that present unique clinical and management challenges. Although surgery remains the primary tool for tissue diagnosis and decompression, complete gross‐total resection is frequently unfeasible due to the infiltrative nature of these lesions.
Olga M. Sergeenko +5 more
wiley +1 more source
Missing Values in Multivariate Analysis
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1975 Summary This paper presents computational results for some alternative methods of analysing multivariate data with missing values. We recommend an algorithm due to Orchard and Woodbury (1972), which gives an estimator that is maximum likelihood when the data come from a multivariate normal population.
Beale, E. M. L., Little, R. J. A.
openaire +2 more sources