code: def scores_at_thresholds(y_score, n_thresholds=10, start=0.0):
      """
      Binarize scores at increasing thresholds, outputs a binary
      matrix where each row corresponds to the binary labels
      obtained from thresholding. n thresholds are generated
      uniformly from [start, 1.0]
      """
      thresholds = np.linspace(start, 1.0, n_thresholds)
      Y_score = np.tile(y_score, (n_thresholds, 1))
      Y_pred = (Y_score >= thresholds[:, np.newaxis]).astype(int)
      return thresholds, Y_pred
  
file_path: sklearn-evaluation/src/sklearn_evaluation/preprocessing/binarize.py
imports: import numpy
  from sklearn_evaluation import validate
label_desc: Use image node_id 7 for calling a global function with example usage: scores_at_thresholds(y_score, n_thresholds, start) and returns: thresholds,  Y_pred