Results 61 to 70 of about 2,499,784 (284)
Regression SVM for Incomplete Data
Schedae Informaticae, 2017 The use of machine learning methods in the case of incomplete data is an important task in many scientific fields, like medicine, biology, or face recognition. Typically, missing values are substituted with artificial values that are estimated from the known samples, and the classical machine learning algorithms are applied.
Struski, Łukasz +3 more
openaire +3 more sources
Finding Top- $k$ Dominance on Incomplete Big Data Using MapReduce Framework
IEEE Access, 2018 Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes large.
Payam Ezatpoor +3 more
doaj +1 more source
Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network [PDF]
, 2000 The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes.
Granger, Eric +3 more
core +1 more source
Kernel-based system identification from noisy and incomplete input-output data
, 2016 In this contribution, we propose a kernel-based method for the identification of linear systems from noisy and incomplete input-output datasets. We model the impulse response of the system as a Gaussian process whose covariance matrix is given by the ...
Bottegal, Giulio +2 more
core +1 more source
Multivariate Tests with Incomplete Data
The Annals of Statistics, 1983 In the context of a normal model, testing problems with missing data are considered. Tests on means are treated when independent extra data on the first $p_1$ variates of $p$ variates is available in addition to complete data. For testing that the mean of the first $p_1$ variates is zero, the LRT is UMP invariant, but for testing that the whole mean is
Eaton, Morris, Kariya, Takeaki
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT A second allogeneic (allo‐)hematopoietic stem cell transplantation (HSCT2) is a potential curative option for pediatric patients with acute lymphoblastic leukemia (ALL) following relapse after first allogeneic transplantation (HSCT1), but its efficacy is limited by high relapse rates and transplant‐related toxicity in highly pretreated ...
Ava Momm +10 more
wiley +1 more source
Methods to Handle Incomplete Data
MAMC Journal of Medical Sciences, 2020 Context: The major question for data analysis is determining the appropriate analytic approach in the presence of incomplete observations. The most common solution to handle missing data in a data set is imputation, where missing values are estimated and
Vinny Johny +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background/Objectives Outcomes for pediatric relapsed/refractory (R/R) acute myeloid leukemia (AML) remain dismal. CPX‐351, a liposomal formulation of cytarabine and daunorubicin, may have less off‐target toxicities than traditional chemotherapies and has shown improved outcomes for adults with newly diagnosed therapy‐related AML.
Jonathan D. Bender +17 more
wiley +1 more source
A Deep Similarity Metric Method Based on Incomplete Data for Traffic Anomaly Detection in IoT
Applied Sciences, 2019 In recent years, with the development of the Internet of Things (IoT) technology, a large amount of data can be captured from sensors for real-time analysis.
Xu Kang, Bin Song, Fengyao Sun
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteonecrosis (ON) is a debilitating complication of acute lymphoblastic leukemia (ALL) therapy. While numerous studies have explored its incidence and associated risk factors, investigations using large‐scale cohorts remain important to characterize ON across heterogeneous populations.
Noémie de Villiers +5 more
wiley +1 more source