Tree Ensemble Featurization Transform

The documentation is generated based on the sources available at dotnet/machinelearning and released under MIT License.

Type: datatransform Aliases: TreeFeat, TreeFeaturizationTransform Namespace: Microsoft.ML.Runtime.Data Assembly: Microsoft.ML.FastTree.dll Microsoft Documentation: Tree Ensemble Featurization Transform


Trains a tree ensemble, or loads it from a file, then maps a numeric feature vector to three outputs: 1. A vector containing the individual tree outputs of the tree ensemble. 2. A vector indicating the leaves that the feature vector falls on in the tree ensemble. 3. A vector indicating the paths that the feature vector falls on in the tree ensemble. If a both a model file and a trainer are specified - will use the model file. If neither are specified, will train a default FastTree model. This can handle key labels by training a regression model towards their optionally permuted indices.


Name Short name Default Description
customColumn col   Input columns: Columns with custom kinds declared through key assignments, for example, col[Kind]=Name to assign column named ‘Name’ kind ‘Kind’
featureColumn feat Features Column to use for features when scorer is not defined
groupColumn group GroupId Column to use for grouping
labelColumn lab Label Column to use for labels
labelPermutationSeed lps 0 If specified, determines the permutation seed for applying this featurizer to a multiclass problem.
nameColumn name Name Name column name
suffix ex   Output column: The suffix to append to the default column names
trainedModelFile in   Predictor model file used in scoring
trainer tr   Trainer to use
weightColumn weight Weight Column to use for example weight