Results 41 to 50 of about 967,885 (269)
Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021 Classification of ordinal data is part of categorical data. Ordinal data consists of features with values based on order or ranking. The use of machine learning methods in Human Resources Management is intended to support decision-making based on ...
I Ketut Adi Wirayasa +3 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed +5 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cyclophosphamide (CY) is associated with potentially fatal cardiotoxicity, yet no electrocardiographic indices have been established for early detection of CY‐induced cardiomyopathy. This study aimed to determine whether corrected QT interval (QTc) prolongation can predict early onset of CY‐related cardiac dysfunction in pediatric ...
Junpei Kawamura +5 more
wiley +1 more source
Non-Parametric Tolerance Limits
The Annals of Mathematical Statistics, 1948 In this note are presented graphs of minimum probable population coverage by sample blocks determined by the order statistics of a sample from a population with a continuous but unknown cumulative distribution function (c.d.f.). The graphs are constructed for the three tolerance levels .90, .95, and .99.
openaire +3 more sources
Hypothesis testing for two population means: parametric or non-parametric test?
, 2019 The parametric Welch $t$-test and the non-parametric Wilcoxon-Mann-Whitney test are the most commonly used two independent sample means tests. More recent testing approaches include the non-parametric, empirical likelihood and exponential empirical ...
Alenazi, Abdulaziz +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser +6 more
wiley +1 more source
Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery
Journal of Causal Inference, 2019 Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one of the most popular CI tests in the non-parametric setting, but many ...
Strobl Eric V. +2 more
doaj +1 more source
Gaussian Control Barrier Functions: Non-Parametric Paradigm to Safety
IEEE Access, 2022 Inspired by the success of control barrier functions (CBFs) in addressing safety, and the rise of data-driven techniques for modeling functions, we propose a non-parametric approach for online synthesis of CBFs using Gaussian Processes (GPs). A dynamical
Mouhyemen A. Khan +2 more
doaj +1 more source
, 2015 A non-parametric technique for modeling the behavior of power amplifiers is presented. The proposed technique relies on the principles of density estimation using the kernel method and is suited for use in power amplifier modeling.
Handel, Peter +3 more
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