Results 11 to 20 of about 6,070,042 (338)

Knowledge and Awareness: Linear Regression [PDF]

Educational Process: International Journal, 2016
Knowledge and awareness are factors guiding development of an individual. These may seem simple and practicable, but in reality a proper combination of these is a complex task.
Monika Raghuvanshi
doaj   +1 more source

Tensor Linear Regression: Degeneracy and Solution

IEEE Access, 2021
Tensor regression is an important and useful tool for analyzing multidimensional array data. To deal with high dimensionality, CANDECOMP/PARAFAC (CP) low-rank constraints are often imposed on the coefficient tensor parameter in the (penalized) loss ...
Ya Zhou, Raymond K. W. Wong, Kejun He
doaj   +1 more source

enphysoft/inverse-linear-regression:

, 2021
This site includes MATLAB source codes, used to generate paired data sets, studied at Albert S. Kim, Inverse Sampling of Degenerate Datasets from a Linear Regression Line, arXiv:2108.11477 [stat.ME], https://arxiv.org/abs/2108 ...
Albert S. Kim
core   +1 more source

Secure Collaborative Computing for Linear Regression

Applied Sciences, 2023
Machine learning usually requires a large amount of training data to build useful models. We exploit the mathematical structure of linear regression to develop a secure and privacy-preserving method that allows multiple parties to collaboratively compute
Albert Guan, Chun-Hung Lin, Po-Wen Chi
doaj   +1 more source

Linear regression analysis

Psychiatry and Behavioral Sciences, 2013
Linear regression is an approach to modeling the association between a numeric dependent variable y and one or more independent variables denoted X. The case of one explanatory variable in regression model is called simple linear regression.
Selim Kılıc
doaj   +1 more source

Validating linear restrictions in linear regression models with general error structure [PDF]

, 2006
A new method for testing linear restrictions in linear regression models is suggested. It allows to validate the linear restriction, up to a specified approximation error and with a specified error probability.
Holzmann, Hajo, Min, Aleksey, Czado, Claudia   +2 more
core   +1 more source

Linear regression analysis study

Journal of the Practice of Cardiovascular Sciences, 2018
Linear regression is a statistical procedure for calculating the value of a dependent variable from an independent variable. Linear regression measures the association between two variables.
Khushbu Kumari, Suniti Yadav
doaj   +1 more source

Linear expectile regression under massive data

Fundamental Research, 2021
In this paper, we study the large-scale inference for a linear expectile regression model. To mitigate the computational challenges in the classical asymmetric least squares (ALS) estimation under massive data, we propose a communication-efficient divide
Shanshan Song, Yuanyuan Lin, Yong Zhou
doaj   +1 more source

Clustered linear regression [PDF]

Knowledge-Based Systems, 2002
Clustered linear regression (CLR) is a new machine learning algorithm that improves the accuracy of classical linear regression by partitioning training space into subspaces. CLR makes some assumptions about the domain and the data set. Firstly, target value is assumed to be a function of feature values.
Ari, B., Güvenir H.A.
openaire   +3 more sources

Conditional Linear Regression

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, Brendan Juba, Zongyi Li, Lisa Ruan   +3 more
openaire   +6 more sources