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Performance Prediction for Enhancing Ensemble Learning
(Universidade Federal de Minas GeraisUFMG, 2018-08-31)
Ensembling machine-learned models has shown to be a useful technique for improving the effectiveness of tasks such as classification, ad-hoc retrieval, and recommendation. Stacking, for instance, learns to weight and combine ...
Towards a Strategy for Performance Prediction on Heterogeneous Architectures
(2019-01-01)
Performance prediction of applications has always been a great challenge, even for homogeneous architectures. However, today’s trend is the design of cluster running in a heterogeneous architecture, which increases the ...
Contention-sensitive static performance prediction for parallel distributed applications
(Elsevier Science BvAmsterdamHolanda, 2006)
Time Series Decomposition using Automatic Learning Techniques for Predictive Models
(Institute of Physics Publishing, 2020-01-07)
This paper proposes an innovative way to address real cases of production prediction. This approach consists in the decomposition of original time series into time sub-series according to a group of factors in order to ...
Towards the Grade’s Prediction. A Study of Different Machine Learning Approaches to Predict Grades from Student Interaction Data
There is currently an open problem within the field of Artificial Intelligence applied to the educational field, which is the prediction of students’ grades. This problem aims to predict early school failure and dropout, ...
Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions
(BioMed Central, 2014-07)
BACKGROUND: It is important to accurately determine the performance of peptide:MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected ...