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Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

IEEE Access
In software engineering, deep learning models are increasingly deployed for critical tasks such as bug detection and code review. However, overfitting remains a challenge that affects the quality, reliability, and trustworthiness of software systems that
Hao Li, Gopi Krishnan Rajbahadur, Dayi Lin, Cor-Paul Bezemer, Zhen Ming Jiang   +4 more
doaj   +3 more sources

Overfitting Reduction of Text Classification Based on AdaBELM

Entropy, 2017
Overfitting is an important problem in machine learning. Several algorithms, such as the extreme learning machine (ELM), suffer from this issue when facing high-dimensional sparse data, e.g., in text classification. One common issue is that the extent of
Xiaoyue Feng, Yanchun Liang, Xiaohu Shi, Dong Xu, Xu Wang, Renchu Guan   +5 more
doaj   +3 more sources

Assessment of the Generalization Ability of the ASTM E900-15 Embrittlement Trend Curve by Means of Monte Carlo Cross-Validation

Metals, 2022
The standard ASTM E900-15 provides an analytical expression to determine the transition temperature shift exhibited by Charpy V-notch data at 41-J for irradiated pressure vessel materials as a function of the variables copper, nickel, phosphorus ...
Diego Ferreño, Mark Kirk, Marta Serrano, José A. Sainz-Aja   +3 more
doaj   +1 more source

A Review Unveiling Various Machine Learning Algorithms Adopted for Biohydrogen Productions from Microalgae

Fermentation, 2023
Biohydrogen production from microalgae is a potential alternative energy source that is now intensively being researched. The complex natures of the biological processes involved have afflicted the accuracy of traditional modelling and optimization ...
Mohamad Zulfadhli Ahmad Sobri, Alya Redhwan, Fuad Ameen, Jun Wei Lim, Chin Seng Liew, Guo Ren Mong, Hanita Daud, Rajalingam Sokkalingam, Chii-Dong Ho, Anwar Usman, D. H. Nagaraju, Pasupuleti Visweswara Rao   +11 more
doaj   +1 more source

A Transfer Learning Technique for Inland Chlorophyll-a Concentration Estimation Using Sentinel-3 Imagery

Applied Sciences, 2021
Chlorophyll-a (Chla) concentration, which serves as a phytoplankton substitute in inland waters, is one of the leading indicators for water quality. Generally, water samples are analyzed in professional laboratories, and Chla concentrations are measured ...
Muhammad Aldila Syariz, Chao-Hung Lin, Dewinta Heriza, Umboro Lasminto, Bangun Muljo Sukojo, Lalu Muhamad Jaelani   +5 more
doaj   +1 more source

A Small Target Detection Method Based on Deep Learning With Considerate Feature and Effectively Expanded Sample Size

IEEE Access, 2021
As a basic task in the field of computer vision, target detection has been concerned by many researchers. The performance of target detection method is also directly related to the research in many advanced semantic fields.
Jun Zhang, Yizhen Meng, Zhipeng Chen
doaj   +1 more source

On the Properties of Bias-Variance Decomposition for kNN Regression

Известия Иркутского государственного университета: Серия "Математика", 2023
When choosing the optimal complexity of the method for constructing decision functions, an important tool is the decomposition of the quality criterion into bias and variance.
V. M. Nedel’ko
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Can We Trust Score Plots?

Metabolites, 2020
In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression ...
Marta Bevilacqua, Rasmus Bro
doaj   +1 more source

Modeling and Prediction of Thermal Deformation Errors in Fiber Optic Gyroscopes Based on the TD-Model

Sensors, 2023
For a fiber optic gyroscope, thermal deformation of the fiber coil can introduce additional thermal-induced phase errors, commonly referred to as thermal errors.
Jintao Xu, Ailing Tian, Hui Liu, Ying Liu   +3 more
doaj   +1 more source

Hands-on training about overfitting.

PLoS Computational Biology, 2021
Overfitting is one of the critical problems in developing models by machine learning. With machine learning becoming an essential technology in computational biology, we must include training about overfitting in all courses that introduce this ...
Janez Demšar, Blaž Zupan
doaj   +1 more source