Precision is ill-defined

[alphawolf1988]

Hello,

i'm currentlyx playing around with features and stumbling over the following message:

Train 'high_20_lc'. Algorithm lc. Label: high_20. Train length 525600. Train columns 9
C:\Users\Christian\miniconda3\envs\trading-bot\lib\site-packages\sklearn\metrics\_classification.py:1469: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use `zero_division` parameter to control this behavior.
  _warn_prf(average, modifier, msg_start, len(result))
Train 'low_20_lc'. Algorithm lc. Label: low_20. Train length 525600. Train columns 9
C:\Users\Christian\miniconda3\envs\trading-bot\lib\site-packages\sklearn\metrics\_classification.py:1469: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use `zero_division` parameter to control this behavior.
  _warn_prf(average, modifier, msg_start, len(result))

That error appears when i comment out the feature:

// {"column_prefix": "", "generator": "talib", "feature_prefix": "", "config": {"columns": ["close"], "functions": ["STDDEV"], "windows": [5, 10, 15, 60]}}

Part of my config is:

// === GENERATE FEATURES ===

    "feature_sets": [
        {"column_prefix": "", "generator": "talib", "feature_prefix": "", "config":  {"columns": ["close"], "functions": ["SMA"], "windows": [5, 8, 13]}},
        {"column_prefix": "", "generator": "talib", "feature_prefix": "", "config":  {"columns": ["close"], "functions": ["EMA"], "windows": [5, 10]}},
        {"column_prefix": "", "generator": "talib", "feature_prefix": "", "config":  {"columns": ["close"], "functions": ["LINEARREG_SLOPE"], "windows": [5, 10, 15, 60]}}
        // {"column_prefix": "", "generator": "talib", "feature_prefix": "", "config":  {"columns": ["close"], "functions": ["STDDEV"], "windows": [5, 10, 15, 60]}}
        // {"column_prefix": "", "generator": "common.my_feature_example:my_feature_example", "feature_prefix": "", "config":  {"columns": "close", "function": "add", "parameter": 2.0, "names": "close_add"}}
    ],

    // === LABELS ===

    "label_sets": [
        {"column_prefix": "", "generator": "highlow2", "feature_prefix": "", "config":  {"columns": ["close", "high", "low"], "function": "high", "thresholds": [2.0], "tolerance": 0.2, "horizon": 120, "names": ["high_20"]}},
        {"column_prefix": "", "generator": "highlow2", "feature_prefix": "", "config":  {"columns": ["close", "high", "low"], "function": "low", "thresholds": [2.0], "tolerance": 0.2, "horizon": 120, "names": ["low_20"]}}
    ],

    // === TRAIN ===

    "label_horizon": 120,  // Batch/offline: do not use these last rows because their labels might not be correct
    "train_length": 525600,  // Batch/offline: Uses this number of rows for training (if not additionally limited by the algorithm)

    "train_feature_sets": [
    {
        "generator": "train_features", "config": {
        // Use values from the attributes: train_features, labels, algorithms
    }}
    ],

    "train_features": [
        "close_SMA_5", "close_SMA_8", "close_SMA_13",
        "close_EMA_5", "close_EMA_10",
        "close_LINEARREG_SLOPE_5", "close_LINEARREG_SLOPE_10", "close_LINEARREG_SLOPE_15", "close_LINEARREG_SLOPE_60"
      //  "close_STDDEV_5", "close_STDDEV_10", "close_STDDEV_15", "close_STDDEV_60"
    ],

    "labels": ["high_20", "low_20"],

    "algorithms": [
        {
            "name": "lc",  // Unique name will be used as a column suffix
            "algo": "lc",  // Algorithm type is used to choose the train/predict function
            "params": {"penalty": "l2", "C": 1.0, "class_weight": null, "solver": "sag", "max_iter": 100},
            "train": {"is_scale": true, "length": 1000000, "shifts": []},
            "predict": {"length": 1440}
        }
    ],

Any idea what i'm doing wrong?

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