Machine learning advances for time series forecasting
Year of publication: |
[2020]
|
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Authors: | Masini, Ricardo P. ; Medeiros, Marcelo C. ; Mendes, Eduardo F. |
Publisher: |
Rio de Janeiro, RJ : Departamento de Economia, Pontifícia Universidade Católica do Rio de Janeiro |
Subject: | Machine learning | statistical learning theory | penalized regressions | regularization | sieve approximation | nonlinear models | neural networks | deep learning | regression trees | random forests | boosting | bagging | forecasting | Künstliche Intelligenz | Artificial intelligence | Neuronale Netze | Neural networks | Prognoseverfahren | Forecasting model | Regressionsanalyse | Regression analysis | Lernprozess | Learning process | Nichtlineare Regression | Nonlinear regression | Lernen | Learning | Zeitreihenanalyse | Time series analysis | Schätztheorie | Estimation theory |
Extent: | 1 Online-Ressource (circa 43 Seiten) Illustrationen |
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Series: | Texto para discussão / Pontifícia Universidade Católica do Rio de Janeiro, Departamento de Economia. - Rio de Janeiro : [Verlag nicht ermittelbar], ZDB-ID 2451506-1. - Vol. no. 679 |
Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper |
Language: | English |
Other identifiers: | hdl:10419/249727 [Handle] |
Classification: | C22 - Time-Series Models |
Source: | ECONIS - Online Catalogue of the ZBW |
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