Results 61 to 70 of about 28,744 (310)

A General Family of Penalties for Combining Differing Types of Penalties in Generalized Structured Models [PDF]

, 2013
Penalized estimation has become an established tool for regularization and model selection in regression models. A variety of penalties with specific features are available and effective algorithms for specific penalties have been proposed.
Oelker, Margret-Ruth, Tutz, Gerhard
core   +2 more sources

AI‐Assisted Self‐Powered Wearable Dual‐Mode Sensor With TENG and Stretchable Optical Fiber for Neurological Disorder Diagnostics

Advanced Science, EarlyView.
This manuscript presents the WDMS platform, an AI‐assisted, self‐powered wearable dual‐mode sensor for tele‐neurology. It integrates a contact–separation TENG insole with stretchable polyurethane optical‐fiber strain sensors to synchronously track plantar pressure and lower‐limb muscle deformation.
Tianliang Li, Han Liu, Guoxu Liu, Qian'ao Wang, Haotian Zhou, Guiyi Liu, Yan Xu, Jun Wang, Zuqiang Wang, Feng Zhu, Feiling Luo, Zhong Lin Wang, Chi Zhang   +12 more
wiley   +1 more source

Regularisasi model pembelajaran mesin dengan regresi terpenalti pada data yang mengandung multikolinearitas (Studi kasus prediksi Indeks Pembangunan Manusia di 34 provinsi di Indonesia)

Majalah Ilmiah Matematika dan Statistika
This research intends to model high-dimensional data that contains multicollinearity in four machine-learning algorithms: Random Forest, K-Nearest Neighbor, XGBoost, and Regression Tree.
Nur Khamidah, Kusman Sadik, Agus M Soleh, Gerry Alfa Dito   +3 more
doaj   +1 more source

An elastic net-regularized HMAX model of visual processing [PDF]

2nd IET International Conference on Intelligent Signal Processing 2015 (ISP), 2015
The hierarchical MAX (HMAX) model of human visual system has been used in robotics and autonomous systems widely. However, there is still a stark gap between human and robotic vision in observing the environment and intelligently categorizing the objects. Therefore, improving models such as the HMAX is still topical.
A. Alameer, G. Ghazaeil, P. Degenaar, K. Nazarpour   +3 more
openaire   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

The Impact of the L1/L2 Ratio on Selection Stability and Solution Sparsity along the Elastic Net Regularization Path in High-Dimensional Genomic Data

Journal of Applied Informatics and Computing
High-dimensional genomic datasets (p>n) pose persistent challenges for predictive modeling and biomarker-oriented feature selection due to multicollinearity and instability of selected feature sets under resampling. Although Elastic Net is widely used to
Fani Fahira, Kusman Sadik, Cici Suhaeni, Agus M Soleh   +3 more
doaj   +1 more source

Sparse Logistic Regression With L1/2 Penalty for Emotion Recognition in Electroencephalography Classification

Frontiers in Neuroinformatics, 2020
Emotion recognition based on electroencephalography (EEG) signals is a current focus in brain-computer interface research. However, the classification of EEG is difficult owing to large amounts of data and high levels of noise. Therefore, it is important
Dong-Wei Chen, Rui Miao, Zhao-Yong Deng, Yue-Yue Lu, Yong Liang, Lan Huang   +5 more
doaj   +1 more source

Sparse STATIS-Dual via Elastic Net

Mathematics, 2021
Multi-set multivariate data analysis methods provide a way to analyze a series of tables together. In particular, the STATIS-dual method is applied in data tables where individuals can vary from one table to another, but the variables that are analyzed ...
Carmen C. Rodríguez-Martínez, Mitzi Cubilla-Montilla, Purificación Vicente-Galindo, Purificación Galindo-Villardón   +3 more
doaj   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Parameter Estimation of Geographically and Temporally Weighted Elastic Net Ordinal Logistic Regression

Mathematics
Geographically and Temporally Weighted Elastic Net Ordinal Logistic Regression is a parsimonious ordinal logistic regression with consideration of the existence of spatial and temporal effects.
Margaretha Ohyver, Purhadi, Achmad Choiruddin   +2 more
doaj   +1 more source