Results 31 to 40 of about 970,726 (170)
A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts
Econometrics, 2015 This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS ...
Hossein Hassani, Emmanuel Sirimal Silva
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Non-parametric Bayesian modeling of complex networks
, 2013 Modeling structure in complex networks using Bayesian non-parametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data.
Mørup, Morten, Schmidt, Mikkel N.
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Keyed Non-Parametric Hypothesis Tests
, 2020 The recent popularity of machine learning calls for a deeper understanding of AI security. Amongst the numerous AI threats published so far, poisoning attacks currently attract considerable attention.
A Kerckhoffs +7 more
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Q residual non-parametric Distribution on Fault Detection Approach Using Unsupervised LSTM-KDE
International Journal of Prognostics and Health ManagementIt is well known among practitioner, majority collected data from industrial process plant are unlabeled. The collected historical data if utilize, able to provide vital information of process plant condition.
Nur Maisarah Mohd Sobran +1 more
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Frontiers in Environmental Science, 2022 The COVID-19 pandemic is dangerous to people’s lives and livelihoods, creating immediate obstacles for organizations that support impacted populations. This research concentrates on the consequences for local microfinance institutions in Pakistan, which ...
Shaohua Lu +4 more
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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
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NON-PARAMETRIC STATISTICS [PDF]
, 1981 This chapter discusses non-parametric statistics. It discusses some additional uses of the χ 2 distribution. The chapter explains how to test the independence of two criteria of classification and how to test whether the population from which the sampling is done is normal.
H.T. Hayslett, Patrick Murphy
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Adaptive non-parametric estimation in the presence of dependence [PDF]
, 2016 We consider non-parametric estimation problems in the presence of dependent data, notably non-parametric regression with random design and non-parametric density estimation. The proposed estimation procedure is based on a dimension reduction. The minimax
Asin, Nicolas, Johannes, Jan
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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
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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
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