<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper aims at the time-series data analysis. We propose the possibility of adding additional features to the existing time series data set, to improve the prediction performance of the prediction model. The main goal of our research was to find a proper method for building a prediction model for the time-series data, using also machine learning methods. In this phase of research, we aim at the data analysis and proposal of the ways to add additional features to our dataset. In this paper, we aim at adding derived parameters from one of the original features. We also propose incorporating LAG’s into the dataset as new features, to enhance the prediction performance on the time series based data.</p></abstract>

This paper aims at the time-series data analysis. We propose the possibility of adding additional features to the existing time series data set, to improve the prediction performance of the prediction model. The main goal of our research was to find a proper method for building a prediction model for the time-series data, using also machine learning methods. In this phase of research, we aim at the data analysis and proposal of the ways to add additional features to our dataset. In this paper, we aim at adding derived parameters from one of the original features. We also propose incorporating LAG’s into the dataset as new features, to enhance the prediction performance on the time series based data.

Adding Additional Features to Improve Time Series Prediction

Slovak University of Technology in Bratislava

Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics

The Institute of Information Technologies and Telecommunications of NCFU

Research Papers Faculty of Materials Science and Technology Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Adding Additional Features to Improve Time Series Prediction"}

This paper aims at the time-series data analysis. We propose the possibility of adding additional features to the existing time series data set, to improve the...

Adding Additional Features to Improve Time Series Prediction

Online veröffentlicht: 16. Dez. 2019

Seitenbereich: 72 - 78

Eingereicht: 19. Aug. 2019

Akzeptiert: 08. Okt. 2019

DOI: https://doi.org/10.2478/rput-2019-0028

Schlüsselwörter
Time series, Prediction, Machine learning, Statistics

© 2019 Dmitrii Borkin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Adding Additional Features to Improve Time Series Prediction

Online veröffentlicht: 16. Dez. 2019

Seitenbereich: 72 - 78

Eingereicht: 19. Aug. 2019

Akzeptiert: 08. Okt. 2019

DOI: https://doi.org/10.2478/rput-2019-0028

SchlüsselwörterTime series, Prediction, Machine learning, Statistics

© 2019 Dmitrii Borkin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Time series, Prediction, Machine learning, Statistics