fc96a86fc02c184682ecd521a4be5d8694828174622725769612d5190a4b1310

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@@ -90,3 +90,13 @@ classification/UCR/PhonemeSpectra/PhonemeSpectra_TRAIN.ts filter=lfs diff=lfs me
 classification/UCR/SpokenArabicDigits/SpokenArabicDigits_TRAIN.ts filter=lfs diff=lfs merge=lfs -text
 classification/UCR/StarLightCurves/StarLightCurves_TEST.ts filter=lfs diff=lfs merge=lfs -text
 classification/UCR/StarLightCurves/StarLightCurves_TRAIN.ts filter=lfs diff=lfs merge=lfs -text
+classification/UCR/UWaveGestureLibraryAll/UWaveGestureLibraryAll_TEST.ts filter=lfs diff=lfs merge=lfs -text
+classification/UCR/UWaveGestureLibraryX/UWaveGestureLibraryX_TEST.ts filter=lfs diff=lfs merge=lfs -text
+classification/UCR/UWaveGestureLibraryY/UWaveGestureLibraryY_TEST.ts filter=lfs diff=lfs merge=lfs -text
+classification/UCR/UWaveGestureLibraryZ/UWaveGestureLibraryZ_TEST.ts filter=lfs diff=lfs merge=lfs -text
+classification/UCR/Yoga/Yoga_TEST.ts filter=lfs diff=lfs merge=lfs -text
+forecasting/autoformer/electricity.csv filter=lfs diff=lfs merge=lfs -text
+forecasting/autoformer/traffic.csv filter=lfs diff=lfs merge=lfs -text
+forecasting/monash/australian_electricity_demand_dataset.tsf filter=lfs diff=lfs merge=lfs -text
+forecasting/monash/dominick_dataset.tsf filter=lfs diff=lfs merge=lfs -text
+forecasting/monash/electricity_hourly_dataset.tsf filter=lfs diff=lfs merge=lfs -text

classification/UCR/TwoLeadECG/TwoLeadECG_TRAIN.ts

@@ -0,0 +1,35 @@
+#TwoLeadECG is an ECG dataset taken from physionet by Eamonn Keogh.
+#Specifically, the data is from MIT-BIH Long-Term ECG Database
+#(ltdb) Record ltdb/15814, begin at time 420, ending at 1019. The
+#task is to distinguish between signal 0 and signal 1.
+@problemName TwoLeadECG
+@timeStamps false
+@missing false
+@univariate true
+@equalLength true
+@seriesLength 82
+@classLabel true 1 2
+@data
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classification/UCR/UMD/UMD_TRAIN.ts

@@ -0,0 +1,63 @@
+## UMD dataset
+#
+#UMD is a synthetic data set with 3 classes: one class is characterized by a small up bell arising at the initial or final period (Up); one does not have any bell (Middle); one has a small down bell arising at the initial or final period (Down).
+#
+#- Class 1: Up
+#- Class 2: Middle
+#- Class 3: Down
+#
+#Train size: 36
+#
+#Test size: 144
+#
+#Missing value: No
+#
+#Number of classses: 3
+#
+#Time series length: 150
+#
+#Data source: Université Joseph Fourier (Grenoble I), Laboratoire d’informatique de Grenoble(LIG), Equipe AMA
+@problemName UMD
+@timeStamps false
+@missing false
+@univariate true
+@equalLength true
+@seriesLength 150
+@classLabel true 1 2 3
+@data
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