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http://repositorio.ufla.br/jspui/handle/1/58260| Title: | Previsão de séries temporais com máquinas de suporte vetorial |
| Other Titles: | Time series forecast with vector support machines |
| Authors: | Guimarães, Paulo Henrique Sales Sáfadi, Thelma Pereira, Geraldo Magela da Cruz Pereira, Tiago Martins |
| Keywords: | Análise de componentes principais Análise de componentes independentes Análise técnica Principal component analysis Independent components analysis Technical analysis Support vector machine |
| Issue Date: | 11-Aug-2023 |
| Publisher: | Universidade Federal de Lavras |
| Citation: | MARTINS, R. A. Previsão de séries temporais com máquinas de suporte vetorial. 2023. 62 p. Dissertação (Mestrado em Estatística e Experimentação Agropecuária)–Universidade Federal de Lavras, Lavras, 2023. |
| Abstract: | This dissertation uses the Support Vector Machine (SVM) technique combining Principal Components and Independent Components analysis in the evaluation of financial time series. This subject is of great interest to researchers, investors and financial institutions that seek to understand the behavior/influence on decision-making in the price market. It is known that the combination of Principal and Independent Components analysis, together with vector support machines can guarantee better results for the context. As a result, it appears that the PCA - SVR, ICA - SV models showed better accuracy when compared to common models, such as the SVR simply. The results of the MAE, MSE, RMSE, R 2 metrics corroborate the applied models in question. |
| Description: | Arquivo retido, a pedido do autor, até agosto de 2024. |
| URI: | http://repositorio.ufla.br/jspui/handle/1/58260 |
| Appears in Collections: | Estatística e Experimentação Agropecuária - Mestrado (Dissertações) |
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