4 writes to NumGoodRows
Microsoft.ML.StandardTrainers (4)
Standard\LogisticRegression\LbfgsPredictorBase.cs (4)
472NumGoodRows = 0; 535NumGoodRows = cursor.KeptRowCount; 574NumGoodRows = 0; 639NumGoodRows = cursor.KeptRowCount;
17 references to NumGoodRows
Microsoft.ML.StandardTrainers (17)
Standard\LogisticRegression\LbfgsPredictorBase.cs (7)
321? new L1Optimizer(Host, BiasCount, L1Weight / NumGoodRows, MemorySize, DenseOptimizer, null, EnforceNonNegativity) 539ch.Check(NumGoodRows > 0, NoTrainingInstancesMessage); 556OneDalLbfgs.LogisticRegressionCompute(featuresPtr, labelsPtr, weightsPtr, useSampleWeights, betaPtr, NumGoodRows, nFeatures, ClassCount, L1Weight, L2Weight, OptTol, MaxIterations, MemorySize, numThreads); 642ch.Check(NumGoodRows > 0, NoTrainingInstancesMessage); 653if (numThreads > 1 && NumGoodRows / numThreads < 10) 655int numNew = Math.Max(1, (int)NumGoodRows / 100); 664int cinstTot = (int)NumGoodRows;
Standard\LogisticRegression\LogisticRegression.cs (6)
224Contracts.Assert(NumGoodRows > 0); 231ch.Info("Model trained with {0} training examples.", NumGoodRows); 254ch.Info("Residual Deviance: \t{0} (on {1} degrees of freedom)", deviance, Math.Max(NumGoodRows - numParams, 0)); 262ch.Info("Null Deviance: \t{0} (on {1} degrees of freedom)", nullDeviance, NumGoodRows - 1); 312_stats = new ModelStatisticsBase(Host, NumGoodRows, numParams, deviance, nullDeviance); 414_stats = new LinearModelParameterStatistics(Host, NumGoodRows, numParams, deviance, nullDeviance, std, weightsOnly, bias);
Standard\LogisticRegression\MulticlassLogisticRegression.cs (3)
312Contracts.Assert(NumGoodRows > 0); 319ch.Info("Model trained with {0} training examples.", NumGoodRows); 359_stats = new ModelStatisticsBase(Host, NumGoodRows, numParams, deviance, nullDeviance);
Standard\PoissonRegression\PoissonRegression.cs (1)
153return base.DifferentiableFunction(in x, ref gradient, progress) + (float)(_lossNormalizer / NumGoodRows);