4 instantiations of FeatureSubsetModel
Microsoft.ML.Ensemble (4)
Trainer\Binary\EnsembleTrainer.cs (1)
105models.Select(k => new FeatureSubsetModel<float>((TScalarPredictor)k)).ToArray(), combiner);
Trainer\EnsembleTrainerBase.cs (1)
158var model = new FeatureSubsetModel<TOutput>(
Trainer\Multiclass\MulticlassDataPartitionEnsembleTrainer.cs (1)
102models.Select(k => new FeatureSubsetModel<VBuffer<float>>((TVectorPredictor)k)).ToArray(),
Trainer\Regression\RegressionEnsembleTrainer.cs (1)
92models.Select(k => new FeatureSubsetModel<float>((TScalarPredictor)k)).ToArray(), combiner);
62 references to FeatureSubsetModel
Microsoft.ML.Ensemble (62)
OutputCombiners\BaseStacking.cs (4)
123public void Train(List<FeatureSubsetModel<TOutput>> models, RoleMappedData data, IHostEnvironment env) 153TOutput>[] maps, List<FeatureSubsetModel<TOutput>> models) 170List<FeatureSubsetModel<TOutput>> models, Func<float, T> labelConvert) 185var model = models[i];
OutputCombiners\IOutputCombiner.cs (1)
34void Train(List<FeatureSubsetModel<TOutput>> models, RoleMappedData data, IHostEnvironment env);
Selector\DiversityMeasure\BaseDisagreementDiversityMeasure.cs (2)
14public List<ModelDiversityMetric<TOutput>> CalculateDiversityMeasure(IList<FeatureSubsetModel<TOutput>> models, 15ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> predictions)
Selector\DiversityMeasure\ModelDiversityMetric.cs (2)
11public FeatureSubsetModel<TOutput> ModelX { get; set; } 12public FeatureSubsetModel<TOutput> ModelY { get; set; }
Selector\IDiversityMeasure.cs (2)
16List<ModelDiversityMetric<TOutput>> CalculateDiversityMeasure(IList<FeatureSubsetModel<TOutput>> models, 17ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> predictions);
Selector\ISubModelSelector.cs (3)
15IList<FeatureSubsetModel<TOutput>> Prune(IList<FeatureSubsetModel<TOutput>> models); 17void CalculateMetrics(FeatureSubsetModel<TOutput> model, ISubsetSelector subsetSelector, Subset subset,
Selector\SubModelSelector\BaseBestPerformanceSelector.cs (6)
25public override void CalculateMetrics(FeatureSubsetModel<TOutput> model, 31public override IList<FeatureSubsetModel<TOutput>> Prune(IList<FeatureSubsetModel<TOutput>> models) 69private sealed class ModelPerformanceComparer : IComparer<FeatureSubsetModel<TOutput>> 82public int Compare(FeatureSubsetModel<TOutput> x, FeatureSubsetModel<TOutput> y)
Selector\SubModelSelector\BaseDiverseSelector.cs (8)
22private readonly ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> _predictions; 29_predictions = new ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]>(); 37public override void CalculateMetrics(FeatureSubsetModel<TOutput> model, 69public override IList<FeatureSubsetModel<TOutput>> Prune(IList<FeatureSubsetModel<TOutput>> models) 87var selectedModels = new List<FeatureSubsetModel<TOutput>>(); 115public abstract List<ModelDiversityMetric<TOutput>> CalculateDiversityMeasure(IList<FeatureSubsetModel<TOutput>> models, 116ConcurrentDictionary<FeatureSubsetModel<TOutput>, TOutput[]> predictions);
Selector\SubModelSelector\BaseSubModelSelector.cs (5)
28protected void Print(IChannel ch, IList<FeatureSubsetModel<TOutput>> models, string metricName) 34foreach (var model in models) 52public virtual IList<FeatureSubsetModel<TOutput>> Prune(IList<FeatureSubsetModel<TOutput>> models) 72public virtual void CalculateMetrics(FeatureSubsetModel<TOutput> model,
Selector\SubModelSelector\BestDiverseSelectorBinary.cs (2)
41public override List<ModelDiversityMetric<Single>> CalculateDiversityMeasure(IList<FeatureSubsetModel<float>> models, 42ConcurrentDictionary<FeatureSubsetModel<float>, Single[]> predictions)
Selector\SubModelSelector\BestDiverseSelectorMulticlass.cs (2)
42public override List<ModelDiversityMetric<VBuffer<Single>>> CalculateDiversityMeasure(IList<FeatureSubsetModel<VBuffer<float>>> models, 43ConcurrentDictionary<FeatureSubsetModel<VBuffer<float>>, VBuffer<Single>[]> predictions)
Selector\SubModelSelector\BestDiverseSelectorRegression.cs (2)
39public override List<ModelDiversityMetric<Single>> CalculateDiversityMeasure(IList<FeatureSubsetModel<float>> models, 40ConcurrentDictionary<FeatureSubsetModel<float>, Single[]> predictions)
Trainer\Binary\EnsembleTrainer.cs (1)
83private protected override IPredictor CreatePredictor(List<FeatureSubsetModel<float>> models)
Trainer\EnsembleDistributionModelParameters.cs (3)
64FeatureSubsetModel<float>[] models, IOutputCombiner<Single> combiner, Single[] weights = null) 159var model = Models[i]; 197var model = Models[i];
Trainer\EnsembleModelParameters.cs (2)
58FeatureSubsetModel<float>[] models, IOutputCombiner<Single> combiner, Single[] weights = null) 151var model = Models[i];
Trainer\EnsembleModelParametersBase.cs (4)
21private protected readonly FeatureSubsetModel<TOutput>[] Models; 27private protected EnsembleModelParametersBase(IHostEnvironment env, string name, FeatureSubsetModel<TOutput>[] models, 64Models = new FeatureSubsetModel<TOutput>[count]; 110var model = Models[i];
Trainer\EnsembleTrainerBase.cs (9)
137var models = new List<FeatureSubsetModel<TOutput>>(); 145var batchModels = new FeatureSubsetModel<TOutput>[Trainers.Length]; 158var model = new FeatureSubsetModel<TOutput>( 193private protected abstract IPredictor CreatePredictor(List<FeatureSubsetModel<TOutput>> models); 208private protected virtual void PrintMetrics(IChannel ch, List<FeatureSubsetModel<TOutput>> models) 217foreach (var model in models) 221private protected static FeatureSubsetModel<TOutput>[] CreateModels<T>(List<FeatureSubsetModel<TOutput>> models) where T : IPredictorProducing<TOutput> 223var subsetModels = new FeatureSubsetModel<TOutput>[models.Count];
Trainer\Multiclass\EnsembleMulticlassModelParameters.cs (2)
50internal EnsembleMulticlassModelParameters(IHostEnvironment env, FeatureSubsetModel<VBuffer<float>>[] models, 136var model = Models[i];
Trainer\Multiclass\MulticlassDataPartitionEnsembleTrainer.cs (1)
90private protected override IPredictor CreatePredictor(List<FeatureSubsetModel<VBuffer<float>>> models)
Trainer\Regression\RegressionEnsembleTrainer.cs (1)
78private protected override IPredictor CreatePredictor(List<FeatureSubsetModel<float>> models)