Evaluation of regression models: Model assessment, model selection and generalization error
When performing a regression or classification analysis, one needs to specify a statistical
model. This model should avoid the overfitting and underfitting of data, and achieve a low …
model. This model should avoid the overfitting and underfitting of data, and achieve a low …
Ensuring the robustness and reliability of data-driven knowledge discovery models in production and manufacturing
The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a widely accepted
framework in production and manufacturing. This data-driven knowledge discovery …
framework in production and manufacturing. This data-driven knowledge discovery …
Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction
Accurate credit risk prediction can help companies avoid bankruptcies and make
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment …
To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE)
model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate …
model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate …
Artificial intelligence: A clarification of misconceptions, myths and desired status
The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes
and ambitious goals the field progressed through various stages of popularity and has …
and ambitious goals the field progressed through various stages of popularity and has …
Histological improvements following energy restriction and exercise: The role of insulin resistance in resolution of MASH
Background & Aims Metabolic dysfunction-associated steatohepatitis (MASH) is one of the
most common liver diseases worldwide and is characterized by multi-tissue insulin …
most common liver diseases worldwide and is characterized by multi-tissue insulin …
LASSO regression modeling on prediction of medical terms among seafarers' health documents using tidy text mining
Generally, seafarers face a higher risk of illnesses and accidents than land workers. In most
cases, there are no medical professionals on board seagoing vessels, which makes disease …
cases, there are no medical professionals on board seagoing vessels, which makes disease …
Virtual metrology in semiconductor manufacturing: Current status and future prospects
Abstract Advanced Process Control (APC) has become an increasingly pressing issue for
the semiconductor industry, particularly in the new era of sub-5nm process technology. To …
the semiconductor industry, particularly in the new era of sub-5nm process technology. To …
[HTML][HTML] Toward accurate indoor positioning: An RSS-based fusion of UWB and machine-learning-enhanced WiFi
G Kia, L Ruotsalainen, J Talvitie - Sensors, 2022 - mdpi.com
A wide variety of sensors and devices are used in indoor positioning scenarios to improve
localization accuracy and overcome harsh radio propagation conditions. The availability of …
localization accuracy and overcome harsh radio propagation conditions. The availability of …
Applying advanced data analytics on pregnancy complications to predict miscarriage with explainable AI
Pregnancy complications in the early months of the family process can lead to miscarriage.
Miscarriage does not occur due to only one reason; many factors are involved in causing …
Miscarriage does not occur due to only one reason; many factors are involved in causing …