Results 21 to 30 of about 110,596 (265)
Entropy, 2023 Compressive sensing is a sub-Nyquist sampling technique for efficient signal acquisition and reconstruction of sparse or compressible signals. In order to account for the sparsity of the underlying signal of interest, it is common to use sparsifying ...
Mohammad Shekaramiz, Todd K. Moon
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IEEE Access, 2023 Prediction of work Travel mode choice is one of the most important parts of travel demand forecasting. Planners can achieve sustainability goals by accurately forecasting how people will get to and from work.
Mahdi Aghaabbasi +4 more
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, 2021 Table detailing the LR, RF, SVM and DNN models’ hyperparameters.
Tingting Zhu (334564) +8 more
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Hyperparameters for final models
, 2022 Selected hyperparameters for elastic net models fit using various -omics data types data on the TCGA dataset. Hyperparameter selection procedure is described in the "supplementary information" section of the paper: https://greenelab.github.io/mpmp ...
Jake Crawford (11084724)
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Hyperparameters tuning of random forest with harmony search in credit scoring [PDF]
, 2019 Correct identification of defaulters and non-defaulters in the lending industry is a crucial task for financial institutions. Credit scoring is a tool utilized for credit granting decisions.
Goh, Rui Ying +2 more
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Nonlinear Hyperparameter Optimization of a Neural Network in Image Processing for Micromachines
Micromachines, 2021 Deep neural networks are widely used in the field of image processing for micromachines, such as in 3D shape detection in microelectronic high-speed dispensing and object detection in microrobots.
Mingming Shen +4 more
doaj +1 more source
Optimal hyperparameters for maxCT.
, 2022 Optimal hyperparameters for maxCT.
Lawrence Whiting (14210044) +6 more
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