3 instantiations of KMeansTrainer
Microsoft.ML.KMeansClustering (3)
KMeansCatalog.cs (2)
44return new KMeansTrainer(env, options); 64return new KMeansTrainer(env, options);
KMeansPlusPlusTrainer.cs (1)
299() => new KMeansTrainer(host, input),
33 references to KMeansTrainer
Microsoft.ML.IntegrationTests (4)
Evaluation.cs (1)
125.Append(mlContext.Clustering.Trainers.KMeans(new KMeansTrainer.Options { NumberOfThreads = 1 }));
IntrospectiveTraining.cs (2)
421new KMeansTrainer.Options 423InitializationAlgorithm = KMeansTrainer.InitializationAlgorithm.Random,
ONNX.cs (1)
94new KMeansTrainer.Options { NumberOfThreads = 1, MaximumNumberOfIterations = 10 }));
Microsoft.ML.KMeansClustering (20)
KMeansCatalog.cs (7)
18/// Train a KMeans++ clustering algorithm using <see cref="KMeansTrainer"/>. 30public static KMeansTrainer KMeans(this ClusteringCatalog.ClusteringTrainers catalog, 33int numberOfClusters = KMeansTrainer.Defaults.NumberOfClusters) 38var options = new KMeansTrainer.Options 48/// Train a KMeans++ clustering algorithm using <see cref="KMeansTrainer"/>. 58public static KMeansTrainer KMeans(this ClusteringCatalog.ClusteringTrainers catalog, KMeansTrainer.Options options)
KMeansPlusPlusTrainer.cs (13)
19[assembly: LoadableClass(KMeansTrainer.Summary, typeof(KMeansTrainer), typeof(KMeansTrainer.Options), 21KMeansTrainer.UserNameValue, 22KMeansTrainer.LoadNameValue, 23KMeansTrainer.ShortName, "KMeans")] 25[assembly: LoadableClass(typeof(void), typeof(KMeansTrainer), null, typeof(SignatureEntryPointModule), "KMeans")] 78/// <seealso cref="Microsoft.ML.Trainers.KMeansTrainer" /> 103/// Options for the <see cref="KMeansTrainer"/> as used in [KMeansTrainer(Options)](xref:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)). 166/// Initializes a new instance of <see cref="KMeansTrainer"/> 793ch.CheckUserArg(numThreads > 0, nameof(KMeansTrainer.Options.NumberOfThreads), "Must be positive"); 794ch.CheckUserArg(k > 0, nameof(KMeansTrainer.Options.NumberOfClusters), "Must be positive"); 796ch.CheckUserArg(accelMemBudgetMb >= 0, nameof(KMeansTrainer.Options.AccelerationMemoryBudgetMb), "Must be non-negative");
Microsoft.ML.Samples (3)
Dynamic\Trainers\Clustering\KMeans.cs (1)
27var pipeline = mlContext.Clustering.Trainers.KMeans(
Dynamic\Trainers\Clustering\KMeansWithOptions.cs (2)
28var options = new KMeansTrainer.Options 36var pipeline = mlContext.Clustering.Trainers.KMeans(options);
Microsoft.ML.Tests (6)
OnnxConversionTest.cs (2)
154Append(mlContext.Clustering.Trainers.KMeans(new Trainers.KMeansTrainer.Options 160InitializationAlgorithm = Trainers.KMeansTrainer.InitializationAlgorithm.Random
Scenarios\ClusteringTests.cs (1)
66var pipe = mlContext.Clustering.Trainers.KMeans("Features", numberOfClusters: k);
TrainerEstimators\TrainerEstimators.cs (3)
74var pipeline = new KMeansTrainer(Env, new KMeansTrainer.Options 78InitializationAlgorithm = KMeansTrainer.InitializationAlgorithm.KMeansYinyang,