Results 1 to 10 of about 127,719 (261)
Improving Genomic Prediction with Machine Learning Incorporating TPE for Hyperparameters Optimization [PDF]
Depending on excellent prediction ability, machine learning has been considered the most powerful implement to analyze high-throughput sequencing genome data.
Mang Liang +11 more
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Parsimonious Optimization of Multitask Neural Network Hyperparameters [PDF]
Neural networks are rapidly gaining popularity in chemical modeling and Quantitative Structure–Activity Relationship (QSAR) thanks to their ability to handle multitask problems.
Cecile Valsecchi +5 more
doaj +3 more sources
Combining K-fold cross validation with bayesian hyperparameter optimization for accuracy enhancement of land cover and land use classification [PDF]
Land cover and land use (LCLU) information is crucial in different earth observation applications, such as environmental management, infrastructure planning, and urban development.
Pooya Heidari, Asghar Milan
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Deep Reinforcement Learning (DRL) enables agents to make decisions based on a well-designed reward function that suites a particular environment without any prior knowledge related to a given environment.
Nesma M Ashraf +3 more
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Enhancing Load Prediction Accuracy using Optimized Support Vector Regression Models
This paper investigates the effect of Support Vector Regression hyperparameters optimization on electrical load prediction. Accurate and robust load prediction helps policy makers in the energy sector to make inform decision and reduce losses.
Abdulsemiu Olawuyi +3 more
doaj +1 more source
Building energy optimization (BEO) is a promising technique to achieve energy efficient designs. The efficacy of optimization algorithms is imperative for the BEO technique and is significantly dependent on the algorithm hyperparameters.
Binghui Si, Feng Liu, Yanxia Li
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In machine learning-based landslide susceptibility assessment, there are some differences in the evaluation results obtained by using different hyperparameters.
Can Yang +4 more
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Hyperparameter Optimization of CNN for Map Building
This article describes an approach for solving the task of finding hyperparameters of an artificial neural network, which is used for making a 2D land map.
Alexandra Akinina, Mikhail Nikiforov
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Global optimization of hyper-parameters in reservoir computing
Reservoir computing has emerged as a powerful and efficient machine learning tool especially in the reconstruction of many complex systems even for chaotic systems only based on the observational data.
Bin Ren, Huanfei Ma
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RHOASo: An Early Stop Hyper-Parameter Optimization Algorithm
This work proposes a new algorithm for optimizing hyper-parameters of a machine learning algorithm, RHOASo, based on conditional optimization of concave asymptotic functions.
Ángel Luis Muñoz Castañeda +2 more
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