3 instantiations of LbfgsLogisticRegressionBinaryTrainer
Microsoft.ML.StandardTrainers (3)
Standard\LogisticRegression\LogisticRegression.cs (1)
474() => new LbfgsLogisticRegressionBinaryTrainer(host, input),
StandardTrainersCatalog.cs (2)
555return new LbfgsLogisticRegressionBinaryTrainer(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, historySize, enforceNonNegativity); 576return new LbfgsLogisticRegressionBinaryTrainer(env, options);
82 references to LbfgsLogisticRegressionBinaryTrainer
Microsoft.ML.AutoML (11)
API\AutoCatalog.cs (3)
324/// <param name="useLbfgsLogisticRegression">true if use <see cref="LbfgsLogisticRegressionBinaryTrainer"/> as available trainer.</param> 334/// <param name="lbfgsLogisticRegressionSearchSpace">if provided, use it as search space for <see cref="LbfgsLogisticRegressionBinaryTrainer"/>, otherwise the default search space will be used.</param> 416/// <param name="useLbfgsLogisticRegression">true if use <see cref="LbfgsLogisticRegressionBinaryTrainer"/> as available trainer.</param>
API\BinaryClassificationExperiment.cs (1)
122/// See <see cref="LbfgsLogisticRegressionBinaryTrainer"/>.
API\MulticlassClassificationExperiment.cs (1)
106/// <see cref="OneVersusAllTrainer"/> using <see cref="LbfgsLogisticRegressionBinaryTrainer"/>.
SweepableEstimator\Estimators\Lbfgs.cs (3)
49var option = new LbfgsLogisticRegressionBinaryTrainer.Options() 67var option = new LbfgsLogisticRegressionBinaryTrainer.Options() 77var binaryTrainer = context.BinaryClassification.Trainers.LbfgsLogisticRegression(option);
TrainerExtensions\BinaryTrainerExtensions.cs (1)
181var options = TrainerExtensionUtil.CreateOptions<LbfgsLogisticRegressionBinaryTrainer.Options>(sweepParams, columnInfo.LabelColumnName);
TrainerExtensions\MultiTrainerExtensions.cs (2)
136var binaryTrainer = _binaryLearnerCatalogItem.CreateInstance(mlContext, sweepParams, columnInfo) as LbfgsLogisticRegressionBinaryTrainer;
Microsoft.ML.Core.Tests (16)
UnitTests\TestEntryPoints.cs (16)
137var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = trainData.OutputData }).PredictorModel; 367InputBuilder ib1 = new InputBuilder(Env, typeof(LbfgsLogisticRegressionBinaryTrainer.Options), catalog); 372var instance = ib1.GetInstance() as LbfgsLogisticRegressionBinaryTrainer.Options; 425var lrInput = new LbfgsLogisticRegressionBinaryTrainer.Options 432predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1510var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = splitOutput.TestData[0] }).PredictorModel; 1559var lrInput = new LbfgsLogisticRegressionBinaryTrainer.Options 1566predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1825var lrInput = new LbfgsLogisticRegressionBinaryTrainer.Options 1832predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 2158var lrInput = new LbfgsLogisticRegressionBinaryTrainer.Options 2166predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 4249var lrInput = new LbfgsLogisticRegressionBinaryTrainer.Options 4257var model = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel;
Microsoft.ML.IntegrationTests (13)
Evaluation.cs (2)
97new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 })); 303new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 }));
Prediction.cs (5)
53new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 })); 83var pipeline = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression( 84new Trainers.LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 }); 106var pipeline = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression( 107new Trainers.LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 });
Training.cs (6)
227var trainer = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression( 228new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1, MaximumNumberOfIterations = 10 }); 453var binaryClassificationTrainer = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression( 454new LbfgsLogisticRegressionBinaryTrainer.Options { MaximumNumberOfIterations = 10, NumberOfThreads = 1, }); 484var binaryClassificationTrainer = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression( 485new LbfgsLogisticRegressionBinaryTrainer.Options { MaximumNumberOfIterations = 10, NumberOfThreads = 1, });
Microsoft.ML.PerformanceTests (1)
KMeansAndLogisticRegressionBench.cs (1)
42new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));
Microsoft.ML.Predictor.Tests (4)
TestPredictors.cs (4)
777LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options() 785LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
Microsoft.ML.Samples (3)
Dynamic\Trainers\BinaryClassification\LbfgsLogisticRegression.cs (1)
27var pipeline = mlContext.BinaryClassification.Trainers
Dynamic\Trainers\BinaryClassification\LbfgsLogisticRegressionWithOptions.cs (2)
28var options = new LbfgsLogisticRegressionBinaryTrainer.Options() 36var pipeline = mlContext.BinaryClassification.Trainers
Microsoft.ML.SearchSpace.Tests (1)
SearchSpaceTest.cs (1)
292CreateAndVerifyDefaultSearchSpace<LbfgsLogisticRegressionBinaryTrainer.Options>();
Microsoft.ML.StandardTrainers (26)
Standard\LogisticRegression\LogisticRegression.cs (18)
18[assembly: LoadableClass(LbfgsLogisticRegressionBinaryTrainer.Summary, typeof(LbfgsLogisticRegressionBinaryTrainer), typeof(LbfgsLogisticRegressionBinaryTrainer.Options), 20LbfgsLogisticRegressionBinaryTrainer.UserNameValue, 21LbfgsLogisticRegressionBinaryTrainer.LoadNameValue, 22LbfgsLogisticRegressionBinaryTrainer.ShortName, 25[assembly: LoadableClass(typeof(void), typeof(LbfgsLogisticRegressionBinaryTrainer), null, typeof(SignatureEntryPointModule), LbfgsLogisticRegressionBinaryTrainer.LoadNameValue)] 80/// <seealso cref="Microsoft.ML.StandardTrainersCatalog.LbfgsLogisticRegression(BinaryClassificationCatalog.BinaryClassificationTrainers, LbfgsLogisticRegressionBinaryTrainer.Options)"/> 82public sealed partial class LbfgsLogisticRegressionBinaryTrainer : LbfgsTrainerBase<LbfgsLogisticRegressionBinaryTrainer.Options, 93/// Options for the <see cref="LbfgsLogisticRegressionBinaryTrainer"/> as used in 94/// <see cref="Microsoft.ML.StandardTrainersCatalog.LbfgsLogisticRegression(BinaryClassificationCatalog.BinaryClassificationTrainers, LbfgsLogisticRegressionBinaryTrainer.Options)"/> 111/// If you need these calculations, add the Microsoft.ML.Mkl.Components package, and initialize <see cref="LbfgsLogisticRegressionBinaryTrainer.Options.ComputeStandardDeviation"/>. 121/// Initializes a new instance of <see cref="LbfgsLogisticRegressionBinaryTrainer"/> 130/// <param name="memorySize">Memory size for <see cref="LbfgsLogisticRegressionBinaryTrainer"/>. Low=faster, less accurate.</param> 152/// Initializes a new instance of <see cref="LbfgsLogisticRegressionBinaryTrainer"/> 184/// Continues the training of a <see cref="LbfgsLogisticRegressionBinaryTrainer"/> using an already trained <paramref name="modelParameters"/> and returns 492/// If you need these calculations, add the Microsoft.ML.Mkl.Components package, and initialize <see cref="LbfgsLogisticRegressionBinaryTrainer.Options.ComputeStandardDeviation"/>
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
139/// <param name="memorySize">Memory size for <see cref="LbfgsLogisticRegressionBinaryTrainer"/>. Low=faster, less accurate.</param>
Standard\PoissonRegression\PoissonRegression.cs (1)
85/// <param name="memorySize">Memory size for <see cref="LbfgsLogisticRegressionBinaryTrainer"/>. Low=faster, less accurate.</param>
StandardTrainersCatalog.cs (6)
13using LROptions = LbfgsLogisticRegressionBinaryTrainer.Options; 525/// Create <see cref="Trainers.LbfgsLogisticRegressionBinaryTrainer"/>, which predicts a target using a linear binary classification model trained over boolean label data. 534/// <param name="historySize">Memory size for <see cref="Trainers.LbfgsLogisticRegressionBinaryTrainer"/>. Low=faster, less accurate.</param> 543public static LbfgsLogisticRegressionBinaryTrainer LbfgsLogisticRegression(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog, 559/// Create <see cref="Trainers.LbfgsLogisticRegressionBinaryTrainer"/> with advanced options, which predicts a target using a linear binary classification model trained over boolean label data. 570public static LbfgsLogisticRegressionBinaryTrainer LbfgsLogisticRegression(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog, LROptions options)
Microsoft.ML.Tests (7)
CalibratedModelParametersTests.cs (1)
28new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 }).Fit(data);
PermutationFeatureImportanceTests.cs (2)
343new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 }).Fit(data); 417new LbfgsLogisticRegressionBinaryTrainer.Options { NumberOfThreads = 1 }).Fit(data);
Scenarios\OvaTest.cs (1)
36var logReg = mlContext.BinaryClassification.Trainers.LbfgsLogisticRegression();
TrainerEstimators\LbfgsTests.cs (3)
22var trainer = ML.BinaryClassification.Trainers.LbfgsLogisticRegression(); 63pipe = pipe.Append(ML.BinaryClassification.Trainers.LbfgsLogisticRegression(new LbfgsLogisticRegressionBinaryTrainer.Options { ShowTrainingStatistics = true })); 84new LbfgsLogisticRegressionBinaryTrainer.Options