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Metrics to assess the generalisation ability of NILM algorithms

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Transferability Metrics for NILM

This repository is going to contain the implementation of our transferability metrics, which we define in our latest publication: On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load Monitoring

PS: compatible to NILMTK!

from GenLoss import *
from nilmtk.api import API
from file_handler import load_experiment

from nilmtk.disaggregate import FHMMExact, Hart85
from nilmtk_contrib import *

# load dict and execute experiment
experiment = load_experiment(experiment_ID)
api_results = API(experiment)

# assess generalisation abilities
g_loss = mean_generalization_loss(api_results)
auh = accuracy_on_unseen_houses(api_results)

exit()

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