statistical learning
Interfaces between statistical learning and risk management
... between Statistical Learning (Hastie et ...tistical Learning is the bridge between Statistics and Machine Learning, whereas Quantitative Risk Management is concerned about assessing and ...
138
The Elements of Statistical Learning Data Mining, Inference, and Prediction
... • Chapter 18 explores the “p ≫ N ” problem, which is learning in high- dimensional feature spaces. These problems arise in many areas, in- cluding genomic and proteomic studies, and document classification. We ...
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Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques
... The aim of this paper is to describe a new integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous ...
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A statistical learning based approach for parameter fine tuning of metaheuristics
... As in the case of PCS, IPTS aim for an instance-specific tailoring of the parameters. At the same time, these strategies use a fixed set of parameter values, as the PTS, avoiding the need of modifying the metaheuristic ...
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STATISTICAL LEARNING METHODS APPLIED TO ROAD PAVEMENT CLASSIFICATION
... The measurement procedure to evaluate the influence of road surface characteristics on vehicle and traffic noise is designated by Close-Proximity (CPX) method, as described in the ISO 11819-2 draft. This procedure ...
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Big Data - principios, práctica, aplicaciones
... I have borrowed from many sources including conference papers, books and other materials posted in the Internet. These sources are too many to list here, but a few deserve special mention. In no particular order these ...
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Machine learning and statistical techniques : an application to the prediction of insolvency in Spanish non-life insurance companies
... machine learning methods such as the ones tested in this paper (See5 and Rough Set) are more useful in economic analysis, because the models they provide can be easily understood and interpreted by human ...
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A Statistical LearningPattern Recognition Glossary
... or it can be learned directly. The former approach is generative since it models the measurements in each class. It is more work, but it can exploit more prior knowledge, needs less data, is more modular, and can handle ...
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Experiencia y recursos para mejorar la docencia en la Universidad
... En los planes de estudio se hace más hincapié en aspectos intelectuales (latín, física, gramática) en lugar de aspectos humanos como relaciones interpersonales (pareja, hijos, amigos, compañeros), comunicación, gestión ...
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Statistical education in Social Sciences
... (13) MOSCOLONI N. Acerca de cifras y datos en la investigación y en la acción social. En: Anuario del Departamento de Ciencias de la Comunicación. Escuela de Comunicación Social, Facultad de Ciencia política y Relaciones ...
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TítuloStatistical learning in complex and temporal data: distances, two sample testing, clustering, classification and Big Data
... common learning scenario assumptions, we assume the availability of a test set large enough to obtain distributional ...resulting learning models exhibit interesting properties including that they work with ...
182
To Innovate or not to Innovate in the Didactic Second Language Scenario (and How) – that Is the Question?
... Language Learning (MALL) and showing the ef- fectiveness of MALL in second and foreign language ...of learning with educational games and game elements as an effective way to ...combining learning ...
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On Statistical Dynamics Of Evolving Markets
... and statistical patterns of these topological measures, which highly re- semble those of mutualistic networks, we also study the nested structure and the nestedness performance of trade networks across different ...
344
Statistical Techniques for Aggregating Experiments Results
... Whereas statistical aggregation is the best way of combining the results of the experiments identified in a SR [Cochrane; 2008], these techniques cannot always be applied in the current experimental context of SE ...
117
Analysis of ensemble expressive performance in string quartets: a statistical and machine learning approach
... Computational approaches for modeling expressive music performance have produced systems that emulate human expression, but few steps have been taken in the domain of ensemble performance. Polyphonic expression and ...
181
Statistical postprocessing of different variables for airports in Spain using machine learning
... The results of the training for the 5 airports chosen with one of the members of the LAM-EPS AEMET- c SREPS en- semble, member 019, are shown. There is no special reason to choose this member although the results ...
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Regularization for sparsity in statistical analysis and machine learning
... We consider models where the response is the spike firing rate of a single neuron at each time point, and the input variables or predictors are the previous stimuli within a certain time window. Typically, nonlinearity ...
176
Decision tree for early detection of cognitive impairment by community pharmacists / Maria Teresa Climent et al
... machine learning algorithms, a decision tree and a predictive tool have been developed in order to increase the efficiency of the screening methodology, discriminating which features play an important role for an ...
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