rdkit.ML.Scoring.Scoring module — The RDKit 2025.09.6 documentation

# rdkit.ML.Scoring.Scoring module

$Id$

Scoring - Calculate rank statistics

Created by Sereina Riniker, October 2012 after a file from Peter Gedeck, Greg Landrum

param scores: ordered list with descending similarity containing

  active/inactive information

param col: column index in scores where active/inactive information is stored param fractions: list of fractions at which the value shall be calculated param alpha: exponential weight

rdkit.ML.Scoring.Scoring.CalcAUC(scores, col)

  Determines the area under the ROC curve

rdkit.ML.Scoring.Scoring.CalcBEDROC(scores, col, alpha)

  BEDROC original defined here: Truchon, J. & Bayly, C.I. Evaluating Virtual Screening Methods: Good and Bad Metric for the “Early Recognition” Problem. J. Chem. Inf. Model. 47, 488-508 (2007). ** Arguments**

  > > - scores: 2d list or numpy array

  > >     0th index representing sample scores must be in sorted order with low indexes “better” scores[sample_id] = vector of sample data

  > > - col: int

  > >     Index of sample data which reflects true label of a sample scores[sample_id][col] = True iff that sample is active

  > > - alpha: float

  > >     hyper parameter from the initial paper for how much to enrich the top

  > Returns

  >   float BedROC score

rdkit.ML.Scoring.Scoring.CalcEnrichment(scores, col, fractions)

  Determines the enrichment factor for a set of fractions

rdkit.ML.Scoring.Scoring.CalcRIE(scores, col, alpha)

  RIE original definded here: Sheridan, R.P., Singh, S.B., Fluder, E.M. & Kearsley, S.K. Protocols for Bridging the Peptide to Nonpeptide Gap in Topological Similarity Searches. J. Chem. Inf. Comp. Sci. 41, 1395-1406 (2001).

rdkit.ML.Scoring.Scoring.CalcROC(scores, col)

  Determines a ROC curve