Semi-Supervised-Shapelets-Learning

Matlab codes for Semi-Supervised Shapelets Learning

main_entry.m is the code entry, and SSSL.m is the main algorithm. There are two datasets for testing, ItalyPowerDemand and ECG

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
ECG200.mat		ECG200.mat
EM.m		EM.m
F_function.m		F_function.m
ItalyPowerDemand_TEST		ItalyPowerDemand_TEST
ItalyPowerDemand_TRAIN		ItalyPowerDemand_TRAIN
L21_norm.m		L21_norm.m
Phi_function.m		Phi_function.m
README.md		README.md
SSSL.m		SSSL.m
Spectral_timeseries_similarity.m		Spectral_timeseries_similarity.m
cross_validation.m		cross_validation.m
derivation_of_S.m		derivation_of_S.m
derivation_of_SS.m		derivation_of_SS.m
derivation_of_lS.m		derivation_of_lS.m
distance_longseries_shortseries.m		distance_longseries_shortseries.m
distance_timeseries_shapelet.m		distance_timeseries_shapelet.m
ff_function.m		ff_function.m
function_value.m		function_value.m
initialization_s.m		initialization_s.m
kmeans.m		kmeans.m
main_entry.m		main_entry.m
read_file.m		read_file.m
reshape_y_ture.m		reshape_y_ture.m
segment_obtain.m		segment_obtain.m
shapelet_similarity.m		shapelet_similarity.m
test_accuracy.m		test_accuracy.m
update_S.m		update_S.m
update_W.m		update_W.m
update_Y.m		update_Y.m
update_lS.m		update_lS.m
z_regularization.m		z_regularization.m

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