WaveletKNN
Wavelet Based K-Nearest Neighbor Model
The employment of the Wavelet decomposition technique proves to be highly advantageous in the modelling of noisy time series data. Wavelet decomposition technique using the "haar" algorithm has been incorporated to formulate a hybrid Wavelet KNN (K-Nearest Neighbour) model for time series forecasting, as proposed by Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | WaveletKNN_0.1.0.tar.gz |
20.7 KiB |
0.1.0 |
rolling linux/noble R-4.5 | WaveletKNN_0.1.0.tar.gz |
20.6 KiB |
0.1.0 |
rolling source/ R- | WaveletKNN_0.1.0.tar.gz |
2.8 KiB |
0.1.0 |
latest linux/jammy R-4.5 | WaveletKNN_0.1.0.tar.gz |
20.7 KiB |
0.1.0 |
latest linux/noble R-4.5 | WaveletKNN_0.1.0.tar.gz |
20.6 KiB |
0.1.0 |
latest source/ R- | WaveletKNN_0.1.0.tar.gz |
2.8 KiB |
0.1.0 |
2026-04-26 source/ R- | WaveletKNN_0.1.0.tar.gz |
2.8 KiB |
0.1.0 |
2026-04-23 source/ R- | WaveletKNN_0.1.0.tar.gz |
2.8 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | WaveletKNN_0.1.0.zip |
23.5 KiB |
0.1.0 |
2025-04-20 source/ R- | WaveletKNN_0.1.0.tar.gz |
2.8 KiB |