Browsing Faculty of Applied Science by Subject "LASSO"

Browsing Faculty of Applied Science by Subject "LASSO"

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  • Combining Lasso and Liu type estimator in the linear regression model 
    Kayanan, M.; Wijekoon, P. (International Statistical Institute, 21-08-19)
    The Ordinary Least Square Estimator (OLSE) has been widely used to estimate unknown parameters in the linear regression model. Since OLSE produces high variance on the estimates when multicollinearity exists among the ...
  • Efficient feature selection and prediction for automobile dataset 
    Sobana, S.; Yogarajah, B. (Faculty of Applied Science, 2021-09-15)
    Machine learning is currently the most commonly used branch of computer science, and it can guide better decisions and intelligent actions for high-value predictions in real-time. Researchers can use machine learning model ...
  • Generalized Stochastic Restricted LARS Algorithm 
    Kayanan, M.; Wijekoon, P. (Faculty of Science, University of Ruhuna, Sri Lanka, 2022-06-30)
    The Least Absolute Shrinkage and Selection Operator (LASSO) is used to tackle both the multicollinearity issue and the variable selection concurrently in the linear regression model. The Least Angle Regression (LARS) ...
  • Mean square error comparison between ridge and lasso estimators in the Misspecified linear regression model 
    Kayanan, M.; Wijekoon, P. (Postgraduate Institute of Science , University of Peradeniya, Sri Lanka, 09-11-18)
    It is well-known that the Ridge Estimator has been used as an alternative estimator for Ordinary Least Squared Estimator (OLSE) to handle multicollinearity problem in the linear regression model. However, it introduces ...
  • Performance of LASSO and Elastic net estimators in Misspecified Linear Regression Model 
    Kayanan, M.; Wijekoon, P. (Faculty of Science, University of Peradeniya, Sri Lanka, 16-09-19)
    Ridge Estimator (RE) has been used as an alternative estimator for Ordinary Least Squared Estimator (OLSE) to handle multicollinearity problem in the linear regression model. However, it introduces heavy bias when the ...
  • Restricted least angle regression algorithm for lasso 
    Kayanan, M.; Wijekoon, P. (Postgraduate Institute of Science , University of Peradeniya, Sri Lanka, 11-10-19)
    Least Absolute Shrinkage and Selection Operator (LASSO) method has been used for variable selection in the linear regression model when multicollinearity exists among the predictor variables. A popular algorithm to find ...
  • Stochastic Restricted LASSO-Type Estimator in the Linear Regression Model 
    Kayanan, M.; Wijekoon, P. (Hindawi, 30-03-20)
    Among several variable selection methods, LASSO is the most desirable estimation procedure for handling regularization and variable selection simultaneously in the high-dimensional linear regression models when multicollinearity ...

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