Results 121 to 130 of about 173,823 (173)

Combining K-fold cross validation with bayesian hyperparameter optimization for accuracy enhancement of land cover and land use classification. [PDF]

Sci Rep
Heidari P, Milan A.
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RELoc: An Enhanced 3D WiFi Fingerprinting Indoor Localization Algorithm with RFECV Feature Selection. [PDF]

Sensors (Basel)
Ayinla SL, Abd Aziz A, Drieberg M, Susanto M, Laouiti A.   +4 more
europepmc   +1 more source

Reward design and hyperparameter tuning for generalizable deep reinforcement learning agents in autonomous racing. [PDF]

Sci Rep
Kunda NSS, Kc P, Pandey M, Kumaar AAN.
europepmc   +1 more source

Enhancing clinical insights in glioma grading using Bayesian Optimization and Explainable AI. [PDF]

J Genet Eng Biotechnol
Elsayad AM, Elsayad OA.
europepmc   +1 more source

Adaptive deep clustering integrating DINOv2 embeddings, graph attention, and bio-inspired optimization. [PDF]

Sci Rep
Abdrabo M, Refaat H, Abdallah M, Farouk O.   +3 more
europepmc   +1 more source

Tree-based learning for high-fidelity prediction of chaos. [PDF]

Sci Rep
Giammarese A, Rana K, Bollt EM, Malik N.
europepmc   +1 more source

Machine Learning Driven Insights into Socio-Economic, Demographic, and Health Determinants of Type-II Diabetes: A Tuned Hyperparameter Random Forest Model Using NFHS-5 Data.

J Pharm Bioallied Sci
Athwani H, Awasthi K, Athwani M, Pandey R.   +3 more
europepmc   +1 more source

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Reproducible Hyperparameter Optimization

Journal of Computational and Graphical Statistics, 2021
A key issue in machine learning research is the lack of reproducibility. We illustrate what role hyperparameter search plays in this problem and how regular hyperparameter search methods can lead t...
Lars Hertel, Pierre Baldi, Daniel L. Gillen   +2 more
openaire   +1 more source

Hyperparameter Optimization Machines

2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016
Algorithm selection and hyperparameter tuning are omnipresent problems for researchers and practitioners. Hence, it is not surprising that the efforts in automatizing this process using various meta-learning approaches have been increased. Sequential model-based optimization (SMBO) is ne of the most popular frameworks for finding optimal hyperparameter
Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme   +2 more
openaire   +1 more source