APPLICATION OF SIMPLE LINEAR REGRESSION ANALYSIS PROCEDURE FOR POTATO YIELDSekhar, V.Rao, V. SrinivasaUmakrishna, K.Thomson, T.Plant Archives (09725210)
The breaking elongation of rotor-spun yarns has been predicted by using linear regression, artificial neural network and neuro-fuzzy models. Cotton fibre properties measured by high volume instrument and yarn count have been used as inputs to the prediction models. Prediction accuracy is found to ...
Exercise template with both theory and applied questions, as well as interpretation and code upload, about simple linear regression based on a randomly-generated CSV file. Name: lm3 Type: cloze Related: lm, lm2, gaussmarkov Description: Cloze with theory and applied questions about ...
Finally, we compared the six models by analyzing the similarities of the DNA primary sequences presented in Table 1 and selected the optimal one. 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 展开 关键词: DNA random distribution linear regression model distributions' changes condensed matrices ...
An optimization procedure for piecewise linear discriminant analysis is described based on the application of ridge regression techniques. The method is based on the use of a matrix transformation that stabilizes data that exhibit a high degree of collinearity. Linear discriminants computed from collinear...
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Nonparametric regression estimates with censored data: local linear smoothers and their applications. For censored time-to-event data, Beran (unpublished manuscript), followed by Doksum and Yandell (1982, Properties of Regression Estimates Based on Censored... HT Kim,YK Truong - 《Biometrics》 被引...
Squared-loss mutual informationLeast-squares independence regressionThe discovery of non-linear causal relationship under additive non-Gaussian noise models has ... M Yamada,M Sugiyama,J Sese - 《Machine Learning》 被引量: 48发表: 2011年 MISS: a non-linear methodology based on mutual information ...
acceptable magnitude. With this concept, researchers have tried to employ deep neural networks (DNNs) as a nonlinear function approximator (Hornik et al., 1989). Unlike traditional simple feed-forward artificial neural networks (ANNs), the hidden layers of DNNs are sufficiently large using “...
As a mature method for solving linear problems, multiple linear regression (MLR) has been widely used in various fields. Its advantage is that it is more convenient and simple when analyzing a multi-factor model. If the data used is the same as the model, the calculation result is unique,...