Results 21 to 30 of about 1,688,491 (311)
Robust Model Selection in Linear regression [PDF]
Kirkuk Journal of Science, 2007 The research deals with the proposing of robust formula for the accumulate prediction error (APE) criterion which is used in selecting regression model. The proposed formula evaluated with a simulation study.
Dr. Sabah Haseeb Hassan
doaj +1 more source
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).
Walter, Gero, Augustin, Thomas
core +1 more source
Research on linear regression algorithm [PDF]
MATEC Web of ConferencesLinear regression is one of the most widely used predictive models in statistics and machine learning. This paper aims to comprehensively discuss the theoretical basis, mathematical principle and application of linear regression algorithm in various ...
Qu Kecheng
doaj +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 Previous work in machine learning and statistics commonly focuses on building models that capture the vast majority of data, possibly ignoring a segment of the population as outliers. By contrast, we may be interested in finding a segment of the population for which we can find a linear rule capable of achieving more accurate ...
Diego Calderon +3 more
openaire +5 more sources
Benign overfitting in linear regression [PDF]
Proceedings of the National Academy of Sciences, 2020 The phenomenon of benign overfitting is one of the key mysteries uncovered by deep learning methodology: deep neural networks seem to predict well, even with a perfect fit to noisy training data. Motivated by this phenomenon, we consider when a perfect fit to training data in linear regression is compatible with accurate prediction.
Peter L. Bartlett +3 more
openaire +6 more sources
Linear Regression Based Real-Time Filtering
Advances in Electrical and Electronic Engineering, 2013 This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications.
Misel Batmend, Daniela Perdukova
doaj +1 more source
An improved quantum-inspired algorithm for linear regression [PDF]
Quantum, 2022 We give a classical algorithm for linear regression analogous to the quantum matrix inversion algorithm [Harrow, Hassidim, and Lloyd, Physical Review Letters'09] for low-rank matrices [Wossnig, Zhao, and Prakash, Physical Review Letters'18], when the ...
András Gilyén, Zhao Song, Ewin Tang
doaj +1 more source
On the implementation of LIR: the case of simple linear regression with interval data [PDF]
, 2012 This paper considers the problem of simple linear regression with interval-censored data. That is, n pairs of intervals are observed instead of the n pairs of precise values for the two variables (dependent and independent).
Cattaneo, Marco E.G.V. +2 more
core +1 more source
On Optimal Interpolation In Linear Regression
CoRR, 2021 25 pages, 7 figures, to appear in NeurIPS ...
Oravkin, E, Rebeschini, P
openaire +4 more sources
Linear Regression for Heavy Tails
Risks, 2018 There exist several estimators of the regression line in the simple linear regression: Least Squares, Least Absolute Deviation, Right Median, Theil–Sen, Weighted Balance, and Least Trimmed Squares.
Guus Balkema, Paul Embrechts
doaj +1 more source