Model 1.2
- Citation Author(s):
-
Konstantinos Theodorakos
- Submitted by:
- Konstantinos Theodorakos
- Last updated:
Abstract
Model 1.2
Gradient Linear Booster (Python xgboost library)
Monthly (kWh) consumption forecasting?
1. Twelve regression models (one per month).
2. Regression using (daily kWh) consumption extracted features.
From weekend/weekday and full series:
Statistical: median, variance, quantiles, ...
Time-series: autocorrelations, trends, seasonalities, ..
Regression model training: 60% (train),20% (validation), 20% (test).
Change vs Model 1: Linear interpolation on the y labels.
Change vs Model 1.2: Instead of Gradient Boosted Trees (GBT) -> Linear booster.
