30 writes to Desc
Microsoft.ML.Data (8)
Prediction\Calibrator.cs (1)
1461[TlcModule.Component(Name = "PlattCalibrator", FriendlyName = "Platt Calibrator", Aliases = new[] { "Platt", "Sigmoid" }, Desc = "Platt calibration.")]
Utils\LossFunctions.cs (7)
99Desc = "Log loss.")] 208[TlcModule.Component(Name = "HingeLoss", FriendlyName = "Hinge loss", Alias = "Hinge", Desc = "Hinge loss.")] 308Desc = "Smoothed Hinge loss.")] 424[TlcModule.Component(Name = "ExpLoss", FriendlyName = "Exponential Loss", Desc = "Exponential loss.")] 461[TlcModule.Component(Name = "SquaredLoss", FriendlyName = "Squared Loss", Alias = "L2", Desc = "Squared loss.")] 518[TlcModule.Component(Name = "PoissonLoss", FriendlyName = "Poisson Loss", Desc = "Poisson loss.")] 579[TlcModule.Component(Name = "TweedieLoss", FriendlyName = "Tweedie Loss", Alias = "tweedie", Desc = "Tweedie loss.")]
Microsoft.ML.FastTree (10)
FastTreeArguments.cs (4)
62[TlcModule.Component(Name = LoadNameValue, FriendlyName = UserNameValue, Desc = Summary)] 118[TlcModule.Component(Name = LoadNameValue, FriendlyName = UserNameValue, Desc = Summary)] 162[TlcModule.Component(Name = LoadNameValue, FriendlyName = UserNameValue, Desc = Summary)] 221[TlcModule.Component(Name = LoadNameValue, FriendlyName = UserNameValue, Desc = Summary)]
Training\EarlyStoppingCriteria.cs (5)
119[TlcModule.Component(FriendlyName = "Tolerant (TR)", Name = "TR", Desc = "Stop if validation score exceeds threshold value.")] 287Desc = "Stop in case of loss of generality.")] 352[TlcModule.Component(FriendlyName = "Low Progress (LP)", Name = "LP", Desc = "Stops in case of low progress.")] 412[TlcModule.Component(FriendlyName = "Generality to Progress Ratio (PQ)", Name = "PQ", Desc = "Stops in case of generality to progress ration exceeds threshold.")] 471Desc = "Stops in case of consecutive loss in generality.")]
Training\Parallel\SingleTrainer.cs (1)
97[TlcModule.Component(Name = "Single", Desc = "Single node machine learning process.")]
Microsoft.ML.LightGbm (4)
LightGbmArguments.cs (3)
215[TlcModule.Component(Name = Name, FriendlyName = FriendlyName, Desc = "Traditional Gradient Boosting Decision Tree.")] 245[TlcModule.Component(Name = Name, FriendlyName = FriendlyName, Desc = "Dropouts meet Multiple Additive Regresion Trees. See https://arxiv.org/abs/1505.01866")] 321[TlcModule.Component(Name = Name, FriendlyName = FriendlyName, Desc = "Gradient-based One-Side Sampling.")]
Parallel\SingleTrainer.cs (1)
50[TlcModule.Component(Name = "Single", Desc = "Single node machine learning process.")]
Microsoft.ML.Parquet (2)
PartitionedPathParser.cs (2)
77Desc = SimplePartitionedPathParser.Summary, Alias = SimplePartitionedPathParser.ShortName)] 198Desc = ParquetPartitionedPathParser.Summary, Alias = ParquetPartitionedPathParser.ShortName)]
Microsoft.ML.Transforms (6)
Dracula\CMCountTable.cs (1)
178Desc = "Create the count table using the count-min sketch structure, which has a smaller memory footprint, at the expense of" +
Dracula\DictCountTable.cs (1)
139Desc = "Build a dictionary containing the exact count of each categorical feature value.")]
Text\StopWordsRemovingTransformer.cs (2)
55Desc = "Remover with predefined list of stop words.")] 732Desc = "Remover with list of stopwords specified by the user.")]
Text\WordBagTransform.cs (1)
437Desc = "Extracts NGrams from text and convert them to vector using dictionary.")]
Text\WordHashBagProducingTransform.cs (1)
303Desc = "Extracts NGrams from text and convert them to vector using hashing trick.")]
1 reference to Desc
Microsoft.ML.Core (1)
ComponentModel\ComponentCatalog.cs (1)
413Description = attribute.Desc;