class_docstr: Base series annotator.
  
  Parameters
  ----------
  fmt : str {"dense", "sparse"}, optional (default="dense")
      Annotation output format:
      * If "sparse", a sub-series of labels for only the outliers in X is returned,
      * If "dense", a series of labels for all values in X is returned.
  labels : str {"indicator", "score"}, optional (default="indicator")
      Annotation output labels:
      * If "indicator", returned values are boolean, indicating whether a value is an
      outlier,
      * If "score", returned values are floats, giving the outlier score.
  
  Notes
  -----
  Assumes "predict" data is temporal future of "fit"
  Single time series in both, no meta-data.
  
  The base series annotator specifies the methods and method
  signatures that all annotators have to implement.
  
  Specific implementations of these methods is deferred to concrete
  annotators.
docstr: Return scores for predicted annotations on test/deployment data.
  
  Parameters
  ----------
  X : pd.DataFrame
      Data to annotate (time series).
  
  Returns
  -------
  Y : pd.Series
      Scores for sequence X exact format depends on annotation type.
docstr_tok: ["Return","scores","for","predicted","annotations","on","test\/deployment","data",".","Parameters","--","--","--","--","--","X",":","pd.DataFrame","Data","to","annotate","(","time","series",")",".","Returns","--","--","--","-","Y",":","pd.Series","Scores","for","sequence","X","exact","format","depends","on","annotation","type","."]
code: def predict_scores(self, X):
      """Return scores for predicted annotations on test/deployment data.
  
      Parameters
      ----------
      X : pd.DataFrame
          Data to annotate (time series).
  
      Returns
      -------
      Y : pd.Series
          Scores for sequence X exact format depends on annotation type.
      """
      self.check_is_fitted()
      X = check_series(X)
      return self._predict_scores(X)
  
file_path: sktime/sktime/annotation/base/_base.py
imports: from sktime.base import BaseEstimator
  from sktime.utils.validation.annotation import check_fmt, check_labels
  from sktime.utils.validation.series import check_series
label_desc: Use image node_id 4 for calling the BaseSeriesAnnotator obj's underlying member method code with example usage: obj.predict_scores(X) and returns: self