Results 91 to 100 of about 368,237 (276)
IEEE Access, 2018 Optimization of deep learning is no longer an imminent problem, due to various gradient descent methods and the improvements of network structure, including activation functions, the connectivity style, and so on.
Qinghe Zheng +4 more
doaj +1 more source
The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial
, 2019 In this tutorial paper, we first define mean squared error, variance, covariance, and bias of both random variables and classification/predictor models.
Crowley, Mark, Ghojogh, Benyamin
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Control of Overfitting with Physics
EntropyWhile there are many works on the applications of machine learning, not so many of them are trying to understand the theoretical justifications to explain their efficiency. In this work, overfitting control (or generalization property) in machine learning is explained using analogies from physics and biology.
Sergei V. Kozyrev +2 more
openaire +4 more sources
Advanced Materials Technologies, EarlyView.This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
, 2019 Kernel density estimation is a well known method involving a smoothing parameter (the bandwidth) that needs to be tuned by the user. Although this method has been widely used the bandwidth selection remains a challenging issue in terms of balancing ...
Lacour, Claire +3 more
core
Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
Jurnal SisfokomStacked ensemble models (SEMs) remain widely used for integrating multiple learning algorithms into a single predictive system. However, SEMs continue to face challenges such as accuracy limitations, overfitting, high computational expenses, and limited ...
Carolus Borromeus Widiyatmoko +2 more
doaj +1 more source
E-Jurnal Matematika, 2012 Linear regression analysis is one of the parametric statistical methods which utilize the relationship between two or more quantitative variables. In linear regression analysis, there are several assumptions that must be met that is normal distribution ...
KADEK DWI FARMANI +2 more
doaj +1 more source
Specification Overfitting in Artificial Intelligence
Artificial Intelligence ReviewAbstract Machine learning (ML) and artificial intelligence (AI) approaches are often criticized for their inherent bias and for their lack of control, accountability, and transparency. Consequently, regulatory bodies struggle with containing this technology's potential negative side effects.
Benjamin Roth 0001 +4 more
openaire +4 more sources
Advanced Materials Technologies, EarlyView.The hydroporator platform employs controlled hydrodynamic deformation for efficient mRNA and CRISPR/Cas9 delivery into primary human T cells, enabling allogeneic CAR‐T cell manufacturing. It preserves cell functionality and drives potent gene editing, CAR expression, and tumor cytotoxicity, while feature‐based analysis links these functional outcomes ...
Soohyun Jeon +6 more
wiley +1 more source