ttm-r2-etth-finetuned-control/preprocessor_config.json

{
  "categorical_encoder": null,
  "conditional_columns": [],
  "context_length": 512,
  "control_columns": [
    "HUFL",
    "HULL",
    "MUFL",
    "MULL",
    "LUFL",
    "LULL"
  ],
  "encode_categorical": false,
  "feature_extractor_type": "TimeSeriesPreprocessor",
  "freq": "1h",
  "frequency_mapping": {
    "10min": 4,
    "15min": 5,
    "2min": 2,
    "30min": 6,
    "5min": 3,
    "W": 9,
    "d": 8,
    "h": 7,
    "min": 1,
    "oov": 0
  },
  "id_columns": [],
  "observable_columns": [],
  "prediction_length": 96,
  "processor_class": "TimeSeriesPreprocessor",
  "scaler_dict": {
    "0": {
      "copy": true,
      "feature_names_in_": [
        "HUFL",
        "HULL",
        "MUFL",
        "MULL",
        "LUFL",
        "LULL"
      ],
      "mean_": [
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        1.9638457706364187,
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        0.7027733450419731,
        2.9906340412969477,
        0.7704704349555455
      ],
      "n_features_in_": 6,
      "n_samples_seen_": 10452,
      "scale_": [
        6.134403361410595,
        2.1455700413380594,
        5.908511495039344,
        1.9702885996497426,
        1.2502961279520424,
        0.6677933692498211
      ],
      "var_": [
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        1.5632404075718698,
        0.4459479840140279
      ],
      "with_mean": true,
      "with_std": true
    }
  },
  "scaler_type": "standard",
  "scaling": true,
  "scaling_id_columns": [],
  "static_categorical_columns": [],
  "target_columns": [
    "OT"
  ],
  "target_scaler_dict": {
    "0": {
      "copy": true,
      "feature_names_in_": [
        "OT"
      ],
      "mean_": [
        17.292530528345626
      ],
      "n_features_in_": 1,
      "n_samples_seen_": 10452,
      "scale_": [
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      ],
      "var_": [
        72.4824828102247
      ],
      "with_mean": true,
      "with_std": true
    }
  },
  "time_series_task": "forecasting",
  "timestamp_column": "date"
}