Now showing items 1-10 of 751
The impact of commuting time over educational achievement: A machine learning approach
(Universidad de Chile. Facultad de Economía y Negocios, 2018)
Taking advantage of georeferenced data from Chilean students, we estimate the impact of commuting time over academic achievement. As the commuting time is an endogenous variable, we use instrumental variables and fixed ...
Cross-validation based forecasting method: a machine learning approach
Our paper aims to evaluate two novel methods on selecting the best forecasting model or its combination based on a Machine Learning approach. The methods are based on the selection of the ”best” model, or combination of ...
Using metrics from complex networks to evaluate machine translation
(ELSEVIER SCIENCE BV, 2011)
Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex ...
Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques
Discriminative learning of Restricted Boltzmann Machines has been recently introduced as an alternative to provide a self-contained approach for both unsupervised feature learning and classification purposes. However, one ...
A machine learning approach to dengue forecasting: comparing LSTM, Random Forest and Lasso
We used the Infodengue database of incidence and weather time-series, to train predictive models for the weekly number of cases of dengue in 790 cities of Brazil. To overcome a limitation in the length of time-series ...
On the training algorithms for Restricted Boltzmann Machine-Based Models
(Universidade Federal de São CarlosUFSCarPrograma de Pós-graduação em Ciência da ComputaçãoCâmpus São Carlos, 2018-12-05)
Deep learning techniques have been studied extensively in the last years, due to its good results related to essential tasks on a large range of applications, such as speech and face recognition, as well as objects ...
Prediction of druggable proteins using machine learning and systems biology: A mini-review
The emergence of -omics technologies has allowed the collection of vast amounts of data on biological systems. Although, the pace of such collection has been exponential, the impact of these data remains small on many ...
UNORGANIZED MACHINES FOR SEASONAL STREAMFLOW SERIES FORECASTING
(World Scientific Publ Co Pte LtdSingaporeSingapura, 2014)
Um método de aprendizagem seqüencial com filtro de Kalman e Extreme Learning Machine para problemas de regressão e previsão de séries temporais
(Universidade Federal de PernambucoUFPEBrasilPrograma de Pos Graduacao em Ciencia da Computacao, 2016)
HOW FAR do WE GET USING MACHINE LEARNING BLACK-BOXES?
(World Scientific Publ Co Pte Ltd, 2012-03-01)
With several good research groups actively working in machine learning (ML) approaches, we have now the concept of self-containing machine learning solutions that oftentimes work out-of-the-box leading to the concept of ...