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Damage identification based on topology optimization and Lasso regularization
In this paper, we present a damage identification method for small damages based on topology optimization and Lasso regularization. In particular,...
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Towards the Analysis of Regularized Denoising Autoencoder for Biosignal Processing: Lasso Versus Ridge Norms
The use of Internet of Things (IoT) that integrate smart bio sensor devices to the internet and shows individual health in real time. Healthcare...
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Experimental investigations on the applicability of LASSO based sparse recovery for compressively sensed OFDM channel estimation
Owing to its success in 4G, Orthogonal Frequency Division Multiplexing (OFDM) made its contenting presence in 5G communications. To accommodate...
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Joint sparse least squares via generalized fused lasso penalty for identifying nonlinear dynamical systems
This paper proposes a joint sparse least-square model that utilizes a generalized fused lasso penalty to jointly identify governing equations of...
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Robust LASSO and Its Applications in Healthcare Data
We address the development of a robust variable selection procedure using the density power divergence with the least absolute shrinkage and...
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Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm
Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical...
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A Method for Cancer Genomics Feature Selection Based on LASSO-RFE
A more efficient feature selection method was developed to screen genes corresponding to specific cancers to further investigate their pathogenesis....
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A combined deep CNN-lasso regression feature fusion and classification of MLO and CC view mammogram image
Breast cancer is the most frequent disease among women, and it is a serious threat to their lives and well-being. Due to high population expansion,...
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A composite quantile regression long short-term memory network with group lasso for wind turbine anomaly detection
Wind turbine anomaly detection is an important but challenging work. Though deep learning is promising in this filed, it may fail for large error...
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Geographically Weighted Sparse Group Lasso: Local and Global Variable Selections for GWR
This paper deals with the variable selection problem in geographically weighted regression (GWR). GWR is a local estimation method that continuously...
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Prediction of compressive strength of GGBFS and Flyash-based geopolymer composite by linear regression, lasso regression, and ridge regression
This study aims to propose an efficient technique for improving the compressive strength of geopolymer concrete using Flyash and GGBS. Various...
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A Comment on Hansen’s Risk of James-Stein and Lasso Shrinkage
This paper comments on Hansen’s (2016) Risk of James-Stein and Lasso shrinkage. We propose the James-Stein post-Lasso estimator in which Lasso first...
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COVID-19 Risk Prediction with Regularized Discriminant Analysis and Lasso Regression Using Booster Tree
The severe acute respiratory syndrome coronavirus which gives rise to coronavirus disease undergone transformation since the start of the pandemic,...
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A Hybrid Machine Learning Approach for Enhanced Prediction of Breast Cancer with Lasso Method for Feature Extraction
Breast cancer diagnosis remains a crucial area of research due to its frequency and impact on global health. Although machine learning approaches...
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Latin American Presidents on TikTok: Bukele, Lasso, and Maduro
The emergence of new digital platforms has led to the evolution of global communication. Even in the realm of politics, there has been a shift toward...
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Identifying Leading Indicators for Tactical Truck Parts’ Sales Predictions Using LASSO
This paper aimed to identify leading indicators for a case company that supplies truck parts to the European truck aftersales market. We used LASSO...
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Why Geometric Progression in Selecting the LASSO Parameter: A Theoretical Explanation
In situations when we know which inputs are relevant, the least squares method is often the best way to solve linear regression problems. However, in...
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Spatio-Temporal Analysis of Rates Derived from Count Data Using Generalized Fused Lasso Poisson Model
We propose a method to statistically analyze rates obtained from count data in spatio-temporal terms, allowing for regional and temporal comparisons....
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Fuzzy Linear Regression Model Based on Adaptive Lasso Method
In this paper, we propose a fuzzy adaptive lasso (least absolute shrinkage and selection operator) estimate for fuzzy linear regression with crisp...
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Strength prediction models for recycled aggregate concrete using Random Forests, ANN and LASSO
Prediction of concrete strength is essential for proportioning new mixtures and quality affirmation of the concrete manufactured. Moreover, in the...
