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Machine learning approaches for forecasting inflation: empirical evidence from Sri Lanka
Ruhuna Journal of Science, 2023 The aim of this study is to forecast the inflation rate using supervised machine learning models (SMLM). While SMLMs are widely used in various fields, they have also been widely applied to forecast inflation rates.
W.M.S Bandara, W.A.R. De Mel
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Efficient Cross-Validation in ILP [PDF]
, 2001 Cross-validation is a technique used in many different machine learning approaches. Straightforward implementation of this technique has the disadvantage of causing computational overhead. However, it has been shown that this overhead often consists of redundant computations, which can be avoided by performing all folds of the cross-validation in ...
Struyf, Jan, Blockeel, Hendrik
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ECG Arrhythmia Classification using High Order Spectrum and 2D Graph Fourier Transform
Applied Sciences, 2020 Heart diseases are in the front rank among several kinds of life threats, due to its high incidence and mortality. Regarded as a powerful tool in the diagnosis of the cardiac disorder and arrhythmia detection, analysis of electrocardiogram (ECG) signals ...
Shu Liu +3 more
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A theory of cross-validation error [PDF]
Journal of Experimental & Theoretical Artificial Intelligence, 1994 This paper presents a theory of error in cross-validation testing of algorithms for predicting real-valued attributes. The theory justifies the claim that predicting real-valued attributes requires balancing the conflicting demands of simplicity and accuracy. Furthermore, the theory indicates precisely how these conflicting demands must be balanced, in
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Compressed Sensing With Cross Validation [PDF]
IEEE Transactions on Information Theory, 2009 Compressed Sensing decoding algorithms can efficiently recover an N dimensional real-valued vector x to within a factor of its best k-term approximation by taking m = 2klog(N/k) measurements y = Phi x. If the sparsity or approximate sparsity level of x were known, then this theoretical guarantee would imply quality assurance of the resulting compressed
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Remote Sensing, 2019 Accurate estimation of forest aboveground biomass (AGB) is important for carbon accounting. Forest AGB estimation has been conducted with a variety of data sources and prediction methods, but many uncertainties still exist.
Xiaofang Sun +3 more
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An Application of High-Dimensional Statistics to Predictive Modeling of Grade Variability
Geosciences, 2020 The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored ...
Juri Hinz +2 more
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International Journal of Digital Earth, 2022 Precipitation patterns are vital to water resource management and hydrological research, especially in the upper reaches of inland rivers in arid and semiarid areas.
Hong Wang +5 more
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Debt-by-Price Ratio, End-of-Year Economic Growth, and Long-Term Prediction of Stock Returns
Mathematics, 2021 With the prominent role of government debt in economic growth in recent decades, one would expect that government debt alongside economic growth to be a risk factor priced in the time series of stock returns.
Parastoo Mousavi
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Frontiers in Genetics, 2019 In genomic prediction, single-step method has been demonstrated to outperform multi-step methods. This study investigated the efficiency of genomic prediction for seven body measurement traits in Yorkshire population and simulated data using single-step ...
Hailiang Song +4 more
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