Update README.md

README.md

@@ -11,8 +11,199 @@ task_categories:
 pretty_name: Time-Series-Library (TSLib)
 language:
 - en
+size_categories:
+- 100B<n<1T
+
+configs:
+  # ---------- Forecasting: ETT (4 subsets) ----------
+  - config_name: ett-h1
+    description: "ETT long-term forecasting subset ETTh1 (hourly)."
+    data_files:
+      - ETT-small/ETTh1.csv
+
+  - config_name: ett-h2
+    description: "ETT long-term forecasting subset ETTh2 (hourly)."
+    data_files:
+      - ETT-small/ETTh2.csv
+
+  - config_name: ett-m1
+    description: "ETT long-term forecasting subset ETTm1 (15-min)."
+    data_files:
+      - ETT-small/ETTm1.csv
+
+  - config_name: ett-m2
+    description: "ETT long-term forecasting subset ETTm2 (15-min)."
+    data_files:
+      - ETT-small/ETTm2.csv
+
+  # ---------- Forecasting: Electricity / Traffic / Weather / Exchange / ILI ----------
+  - config_name: electricity
+    description: "Electricity load forecasting (UCI Electricity)."
+    data_files:
+      - electricity/electricity.csv
+
+  - config_name: traffic
+    description: "Traffic volume forecasting."
+    data_files:
+      - traffic/traffic.csv
+
+  - config_name: weather
+    description: "Weather time-series forecasting."
+    data_files:
+      - weather/weather.csv
+
+  - config_name: exchange-rate
+    description: "Exchange rate forecasting."
+    data_files:
+      - exchange_rate/exchange_rate.csv
+
+  - config_name: ili
+    description: "Influenza-like illness (ILI) forecasting."
+    data_files:
+      - illness/national_illness.csv
+
+  # ---------- Forecasting (Short-term): M4 (6 subsets) ----------
+  - config_name: m4-yearly
+    description: "M4 Yearly forecasting subset."
+    data_files:
+      - m4/Yearly-train.csv
+      - m4/Yearly-test.csv
+
+  - config_name: m4-quarterly
+    description: "M4 Quarterly forecasting subset."
+    data_files:
+      - m4/Quarterly-train.csv
+      - m4/Quarterly-test.csv
+
+  - config_name: m4-monthly
+    description: "M4 Monthly forecasting subset."
+    data_files:
+      - m4/Monthly-train.csv
+      - m4/Monthly-test.csv
+
+  - config_name: m4-weekly
+    description: "M4 Weekly forecasting subset."
+    data_files:
+      - m4/Weekly-train.csv
+      - m4/Weekly-test.csv
+
+  - config_name: m4-daily
+    description: "M4 Daily forecasting subset."
+    data_files:
+      - m4/Daily-train.csv
+      - m4/Daily-test.csv
+
+  - config_name: m4-hourly
+    description: "M4 Hourly forecasting subset."
+    data_files:
+      - m4/Hourly-train.csv
+      - m4/Hourly-test.csv
+
+  # ---------- Classification: UEA (10 subsets) ----------
+  - config_name: ethanol-concentration
+    description: "UEA multivariate classification: EthanolConcentration."
+    data_files:
+      - EthanolConcentration/EthanolConcentration_TRAIN.ts
+      - EthanolConcentration/EthanolConcentration_TEST.ts
+
+  - config_name: face-detection
+    description: "UEA multivariate classification: FaceDetection."
+    data_files:
+      - FaceDetection/FaceDetection_TRAIN.ts
+      - FaceDetection/FaceDetection_TEST.ts
+
+  - config_name: handwriting
+    description: "UEA multivariate classification: Handwriting."
+    data_files:
+      - Handwriting/Handwriting_TRAIN.ts
+      - Handwriting/Handwriting_TEST.ts
+
+  - config_name: heartbeat
+    description: "UEA multivariate classification: Heartbeat."
+    data_files:
+      - Heartbeat/Heartbeat_TRAIN.ts
+      - Heartbeat/Heartbeat_TEST.ts
+
+  - config_name: japanese-vowels
+    description: "UEA multivariate classification: JapaneseVowels."
+    data_files:
+      - JapaneseVowels/JapaneseVowels_TRAIN.ts
+      - JapaneseVowels/JapaneseVowels_TEST.ts
+
+  - config_name: pems-sf
+    description: "UEA multivariate classification: PEMS-SF."
+    data_files:
+      - PEMS-SF/PEMS-SF_TRAIN.ts
+      - PEMS-SF/PEMS-SF_TEST.ts
+
+  - config_name: self-regulation-scp1
+    description: "UEA multivariate classification: SelfRegulationSCP1."
+    data_files:
+      - SelfRegulationSCP1/SelfRegulationSCP1_TRAIN.ts
+      - SelfRegulationSCP1/SelfRegulationSCP1_TEST.ts
+
+  - config_name: self-regulation-scp2
+    description: "UEA multivariate classification: SelfRegulationSCP2."
+    data_files:
+      - SelfRegulationSCP2/SelfRegulationSCP2_TRAIN.ts
+      - SelfRegulationSCP2/SelfRegulationSCP2_TEST.ts
+
+  - config_name: spoken-arabic-digits
+    description: "UEA multivariate classification: SpokenArabicDigits."
+    data_files:
+      - SpokenArabicDigits/SpokenArabicDigits_TRAIN.ts
+      - SpokenArabicDigits/SpokenArabicDigits_TEST.ts
+
+  - config_name: uwave-gesture-library
+    description: "UEA multivariate classification: UWaveGestureLibrary."
+    data_files:
+      - UWaveGestureLibrary/UWaveGestureLibrary_TRAIN.ts
+      - UWaveGestureLibrary/UWaveGestureLibrary_TEST.ts
+
+  # ---------- Anomaly Detection ----------
+  - config_name: smd
+    description: "Server Machine Dataset (SMD) for anomaly detection."
+    data_files:
+      - SMD/SMD_train.npy
+      - SMD/SMD_test.npy
+      - SMD/SMD_test_label.npy
+      - SMD/SMD_train.pkl
+      - SMD/SMD_test.pkl
+      - SMD/SMD_test_label.pkl
+
+  - config_name: msl
+    description: "NASA Mars Science Laboratory (MSL) anomaly detection."
+    data_files:
+      - MSL/MSL_train.npy
+      - MSL/MSL_test.npy
+      - MSL/MSL_test_label.npy
+
+  - config_name: smap
+    description: "NASA Soil Moisture Active Passive (SMAP) anomaly detection."
+    data_files:
+      - SMAP/SMAP_train.npy
+      - SMAP/SMAP_test.npy
+      - SMAP/SMAP_test_label.npy
+
+  - config_name: psm
+    description: "KPI-based Process/System Monitoring anomaly detection."
+    data_files:
+      - PSM/train.csv
+      - PSM/test.csv
+      - PSM/test_label.csv
+
+  - config_name: swat
+    description: "Secure Water Treatment (SWaT) anomaly detection; CSV are preprocessed, Excel are raw."
+    data_files:
+      - SWaT/swat_train.csv
+      - SWaT/swat_train2.csv
+      - SWaT/swat2.csv
+      - SWaT/swat_raw.csv
+      - SWaT/SWaT_Dataset_Normal_v1.xlsx
+      - SWaT/SWaT_Dataset_Attack_v0.xlsx
 ---
 
+
 # Time-Series-Library (TSLib)
 
 TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.