140var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = model }).ScoredData; 141scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 143var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = lrModel.Apply(Env, trainData.Model) }).ScoredData; 144scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 434ScoreModel.Score(Env, 435new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = predictorModels[i] }) 448ScoreModel.Score(Env, 449new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = avgEnsemble }).ScoredData; 454ScoreModel.Score(Env, 455new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = medEnsemble }).ScoredData; 460ScoreModel.Score(Env, 461new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = regEnsemble }).ScoredData; 1514var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = lrModel }).ScoredData; 1515scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 1517var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = calibratedLrModel }).ScoredData; 1518scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 1536var scoredFf = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = twiceCalibratedFfModel }).ScoredData; 1574ScoreModel.Score(Env, 1575new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = predictorModels[i] }) 1591var binaryScored = ScoreModel.Score(Env, 1592new ScoreModel.Input 1597var binaryScoredCalibrated = ScoreModel.Score(Env, 1598new ScoreModel.Input 1610var regressionScored = ScoreModel.Score(Env, 1611new ScoreModel.Input 1623var anomalyScored = ScoreModel.Score(Env, 1624new ScoreModel.Input 1666var scoredFromSaved = ScoreModel.Score(Env, 1667new ScoreModel.Input() 1840ScoreModel.Score(Env, 1841new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = predictorModels[i] }) 1857var binaryScored = ScoreModel.Score(Env, 1858new ScoreModel.Input 1863var binaryScoredCalibrated = ScoreModel.Score(Env, 1864new ScoreModel.Input 1876var regressionScored = ScoreModel.Score(Env, 1877new ScoreModel.Input 1893var scoredFromSaved = ScoreModel.Score(Env, 1894new ScoreModel.Input() 2025ScoreModel.Score(Env, 2026new ScoreModel.Input { Data = splitOutput.TestData[nModels], PredictorModel = predictorModels[i] }) 2036var mcScored = ScoreModel.Score(Env, 2037new ScoreModel.Input 2053var scoredFromSaved = ScoreModel.Score(Env, 2054new ScoreModel.Input()

11[assembly: LoadableClass(typeof(void), typeof(ScoreModel), null, typeof(SignatureEntryPointModule), "ScoreModel")]

190var args = new ScoreModel.Input(); 204outputMap.Add(nameof(ScoreModel.Output.ScoredData), scoreNodeOutputScoredData.VarName); 205outputMap.Add(nameof(ScoreModel.Output.ScoringTransform), scoreNodeOutputScoringTransform.VarName); 224args = new ScoreModel.Input(); 238outputMap.Add(nameof(ScoreModel.Output.ScoredData), scoreNodeOutputScoredData.VarName); 239outputMap.Add(nameof(ScoreModel.Output.ScoringTransform), scoreNodeOutputScoringTransform.VarName);

674var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, fastTree) }).ScoredData; 689scoredArray[i] = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = fastTrees[i] }).ScoredData; 844var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, predictor) }).ScoredData; 865scoredArray[i] = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = predictors[i] }).ScoredData;