GitHub - Grasia/knnp: Time Series Forecasting using K-Nearest Neighbors Algorithm (Parallel approach) (original) (raw)
knnp : Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)
First release was developed as an End-of-Degree Project.
Further improvements have been made now as a project from GRASIA investigation group:https://grasia.fdi.ucm.es/
Purpose
This package intends to provide R users or anyone interested in the field of time series prediction the possibility of aplying the k-nearest neighbors algorithm to time series prediction problems. Two main functionalities are provided:
- Time series prediction using this method.
- Optimization of parameteres k and d of the algorithm.
All the code involved has been optimized to:
- Parallelize critic components as the process of optimization of parameteres k and d or the calculation of distances.
- Use memory efficiently.
Authors
- Daniel Bastarrica Lacalle
- Javier Berdecio Trigueros
Directors
- Javier Arroyo Gallardo
- Albert Meco Alias
Maintainer
- Daniel Bastarrica Lacalle
License
AGPL-3