Results 21 to 30 of about 10,283,828 (367)
Nonparametric regression analysis [PDF]
, 2015 textNonparametric regression uses nonparametric and flexible methods in analyzing complex data with unknown regression relationships by imposing minimum assumptions on the regression function.
Malloy, Shuling Guo
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Better subset regression [PDF]
, 2013 To find efficient screening methods for high dimensional linear regression models, this paper studies the relationship between model fitting and screening performance.
Xiong, Shifeng
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Bandwidth Selection in Nonparametric Regression with Large Sample Size
Proceedings, 2018 In the context of nonparametric regression estimation, the behaviour of kernel methods such as the Nadaraya-Watson or local linear estimators is heavily influenced by the value of the bandwidth parameter, which determines the trade-off between bias and ...
Daniel Barreiro-Ures +2 more
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Distributed multinomial regression [PDF]
, 2015 This article introduces a model-based approach to distributed computing for multinomial logistic (softmax) regression. We treat counts for each response category as independent Poisson regressions via plug-in estimates for fixed effects shared across ...
Taddy, Matt
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A simple but effective method for Indonesian automatic text summarisation
Connection Science, 2022 Automatic text summarisation (ATS) (therein two main approaches–abstractive summarisation and extractive summarisation are involved) is an automatic procedure for extracting critical information from the text using a specific algorithm or method.
Nankai Lin, Jinxian Li, Shengyi Jiang
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IEEE Access, 2023 In this research, we present an innovative Quadratic Residual Multiplicative Filter Neural Network (QRMFNN) to effectively learn extremely complex sensor signals as a low-dimensional regression problem.
Mustafa Umut Demirezen
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Bayesian Linear Regression [PDF]
, 2009 The paper is concerned with Bayesian analysis under prior-data conflict, i.e. the situation when observed data are rather unexpected under the prior (and the sample size is not large enough to eliminate the influence of the prior).
Augustin, Thomas, Walter, Gero
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Adaptive Huber Regression [PDF]
, 2018 Big data can easily be contaminated by outliers or contain variables with heavy-tailed distributions, which makes many conventional methods inadequate.
Fan, Jianqing, Sun, Qiang, Zhou, Wenxin
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Power curves prediction using empirical data regression on small scale compressed air energy storage
Journal of Mechanical Engineering and Sciences, 2019 The key to optimizing the system is to know the operating point of the system at the time of loading, or it is known as the power curve. However, to identify the power curve, the existing method is to model the mathematical of the system.
Widjonarko +3 more
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Turkish Journal of Agriculture: Food Science and Technology, 2020 Lumbar disc herniation (LDH) is a common cause of low back pain and radicular pain. The aim of our study was to evaluate the regression of LDH in patients who are considered to require surgical treatment but prefer conservative treatment.
Yener Akyuva +6 more
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