Results 271 to 280 of about 589,246 (317)

Ensemble forecasts of COVID-19 activity to support Australia's pandemic response: 2020-22. [PDF]

PLoS Comput Biol
Moss R, Tobin RJ, O'Hara-Wild M, Adekunle AI, Liu D, South T, Morris DJ, Ryan GE, Hao T, Babu A, Senior KL, Wood JG, Golding N, Ross JV, Dawson P, Hyndman RJ, Price DJ, McCaw JM, Shearer FM.   +18 more
europepmc   +1 more source

An integrated machine learning framework for TCM five-flavor classification based on E-tongue profiling and SHAP analysis. [PDF]

Chin Med
Li Z, Meng X, Yang L, Yan X, Li L, Fu Y, Tang J, Zhang S.   +7 more
europepmc   +1 more source

Predictive voting model for early diagnosis of diabetes dataset. [PDF]

Front Cardiovasc Med
Al-Bimani T, AlShaqsi J, Alkhawaldeh R, Al Busaidi AS, Tarhini A.   +4 more
europepmc   +1 more source

A Validation-Driven Explainable Deep Ensemble Framework for Image-Based Saffron Adulteration Detection. [PDF]

Foods
Bukhari SNH, Ogudo KA.
europepmc   +1 more source

Spielplan, Mitteilungen und Notizen

, 1971
Berliner Ensemble
core  

In Search of Shape in the Unshaped: Constructing Ensembles of Intrinsically Disordered Proteins. [PDF]

Biophys Rev (Melville)
Saha D, Yang W, Zheng W.
europepmc   +1 more source

Harnessing hybrid stacking ensemble learning for accurate pulmonary embolism diagnosis using tabular clinical data. [PDF]

Sci Rep
Abdelhamid A, Moustafa HE, Nafea HB, Abdelhay EH, Abo-Zahhad MM, El-Ghamry A.   +5 more
europepmc   +1 more source

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Gaussian Ensemble as an Interpolating Ensemble

Physical Review Letters, 1988
We consider a noncanonical ensemble which involves a sample thermally connected to a finite heat bath with specific properties. Treating the size of the heat bath as a parameter, we show that static properties of finite samples are ensemble dependent.
, Challa, , Hetherington
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From cluster ensemble to structure ensemble

Information Sciences, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhiwen Yu 0002, Jane You, Hau-San Wong, Guoqiang Han 0002   +3 more
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Ensemble Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost.
openaire   +2 more sources