Model 2.1.4

Model 2.1.4 Clustered-meter average monthly ratios Monthly (kWh) consumption clustering: 1. Twelve clustering models (one per month of signup): Spectral Clustering with nearest neighbors.2. Clustering using (daily kWh) consumption extracted features. Cluster count set to 2-4: final count is decided by maximum silhouette score of manhattan distances.3. Meters not in the training clustering data, are classified to a specific cluster using a Gaussian Process Classifier (GPC) on the same dataset (12 classifiers total). Features (170) from weekend/weekday and full series:- Statistical: median, variance, quantiles, ...- Time-series: autocorrelations, trends, seasonalities, ... Forecasting for a meter: Using the median montly consumption + in-cluster month-to-month ratios. Forecasting for a meter: Using the in-cluster month-to-month ratios * non-parametric Kernel Density Estimation resampling.