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Measuring the impact of responsible factors on CO2 emission using generalized additive model (GAM) [PDF]
The indicators of economic and sustainable development ultimately significantly depend on carbon dioxide (CO2) emissions in every country. In Bangladesh, there is an increasing trend in population, industrialization, as well as electricity demand ...
Ruhul Amin +2 more
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As air pollution becomes more and more serious, PM2.5 is the primary pollutant, inevitably attracts wide public attention. Therefore, a novel PM2.5 concentration forecasting method based on linear fuzzy information granule_dynamic time ...
Hong Yang, Han Zhang
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Multi-label Classification Using Vector Generalized Additive Model via Cross-Validation
Multi-label classification is a unique challenge in machine learning designed for two targets with each containing one or multiple classes. This problem can be resolved using several methods, including the classification of the targets individually or ...
Amri Muhaimin +2 more
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Generalized Additive Models [PDF]
The classical linear regression model expresses the response vector Y as a function of the predictor variables \(X_ i\) through the model \(Y=\sum_{i}X_ i\beta_ i+e\), where the \(X_ i\) are observed, the \(\beta_ i\) are estimated by least squares or some other technique, e is the vector of errors.
Hastie, Trevor, Tibshirani, Robert
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Global gold prices forecasting using Bayesian nonparametric quantile generalized additive model [PDF]
Gold is one of the most attractive commodities and popular investments. Investment experts often recommend investing in gold because gold is one of the safest investments.
Yudhie Andriyana +4 more
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The Impact of Climate Change on The Geographic Distribution of Thymus Kotschyanus (Boiss and Hohen) Using Ensemble Modelling [PDF]
This study aimed at predicting the effect of climate change on the geographic distribution of Thymus kotschyanus Boiss and Hohen in Mazandaran province. Species presence data were recorded via the Global Positioning System (GPS).
Samaneh Nazari +3 more
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Functional Generalized Additive Models [PDF]
We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate.
Mathew W, McLean +4 more
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Respiratory syncytial virus (RSV) causes significant childhood morbidity and mortality in the developing world. The determinants of RSV seasonality are of importance in designing interventions.
James Wambua +6 more
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Ground-level ozone (O3) is a key atmospheric gas that controls the oxidizing capacity of the atmosphere and has significant health and environmental implications. Due to ongoing reductions in the concentrations of O3 precursors, it is important to assess
Matthew Ninneman +4 more
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Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications. [PDF]
OBJECTIVE:To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN:Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010.
Paul Thottakkara +6 more
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