54 references to Trainer
Microsoft.ML.AutoML (4)
Experiment\SuggestedPipeline.cs (1)
84
if (pipelineNode.NodeType == PipelineNodeType.
Trainer
)
TrainerExtensions\TrainerExtensionUtil.cs (3)
106
NodeType = PipelineNodeType.
Trainer
,
130
return new PipelineNode(trainerName.ToString(), PipelineNodeType.
Trainer
, DefaultColumnNames.Features,
137
return new PipelineNode(trainerName.ToString(), PipelineNodeType.
Trainer
, DefaultColumnNames.Features,
Microsoft.ML.CodeGenerator (5)
CodeGenerator\CSharp\CodeGenerator.cs (3)
46
var trainerNodes = _pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.
Trainer
);
209
.SkipWhile(t => t.NodeType == PipelineNodeType.
Trainer
) //skip the trainer
256
var node = _pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.
Trainer
).First();
CodeGenerator\CSharp\PipelineExtension.cs (2)
27
.SkipWhile(t => t.NodeType == PipelineNodeType.
Trainer
) //skip the trainer
76
var node = pipeline.Nodes.Where(t => t.NodeType == PipelineNodeType.
Trainer
).First();
Microsoft.ML.CodeGenerator.Tests (45)
ApprovalTests\ConsoleCodeGeneratorTests.cs (2)
560
var matrixPipelineNode = new PipelineNode(nameof(TrainerName.MatrixFactorization), PipelineNodeType.
Trainer
, "Features", "Score", hyperParam);
729
var lightGbmPipelineNode = new PipelineNode(nameof(TrainerName.LightGbmRanking), PipelineNodeType.
Trainer
, "Features", "Score", hyperParam);
CodeGenTests.cs (3)
33
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
54
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
127
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, new string[] { "Label" }, default(string), elementProperties);
TrainerGeneratorTests.cs (40)
35
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
63
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
85
PipelineNode node = new PipelineNode("LightGbmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
103
PipelineNode node = new PipelineNode("SymbolicSgdLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
123
PipelineNode node = new PipelineNode("SymbolicSgdLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
140
PipelineNode node = new PipelineNode("SgdCalibratedBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
160
PipelineNode node = new PipelineNode("SgdCalibratedBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
177
PipelineNode node = new PipelineNode("SdcaLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
197
PipelineNode node = new PipelineNode("SdcaLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
214
PipelineNode node = new PipelineNode("SdcaMaximumEntropyMulti", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
234
PipelineNode node = new PipelineNode("SdcaMaximumEntropyMulti", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
251
PipelineNode node = new PipelineNode("SdcaRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
271
PipelineNode node = new PipelineNode("SdcaRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
287
PipelineNode node = new PipelineNode("MatrixFactorization", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
313
PipelineNode node = new PipelineNode("MatrixFactorization", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
328
PipelineNode node = new PipelineNode("LbfgsPoissonRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
348
PipelineNode node = new PipelineNode("LbfgsPoissonRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
365
PipelineNode node = new PipelineNode("OlsRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
385
PipelineNode node = new PipelineNode("OlsRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
402
PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
422
PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
439
PipelineNode node = new PipelineNode("LbfgsLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
459
PipelineNode node = new PipelineNode("LbfgsLogisticRegressionBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
476
PipelineNode node = new PipelineNode("LbfgsMaximumEntropyMulti", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
496
PipelineNode node = new PipelineNode("LbfgsMaximumEntropyMulti", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
513
PipelineNode node = new PipelineNode("LinearSvmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
533
PipelineNode node = new PipelineNode("LinearSvmBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
551
PipelineNode node = new PipelineNode("FastTreeTweedieRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
571
PipelineNode node = new PipelineNode("OnlineGradientDescentRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
589
PipelineNode node = new PipelineNode("FastTreeRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
609
PipelineNode node = new PipelineNode("FastTreeRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
627
PipelineNode node = new PipelineNode("FastTreeBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
647
PipelineNode node = new PipelineNode("FastTreeBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
665
PipelineNode node = new PipelineNode("FastForestRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
684
PipelineNode node = new PipelineNode("FastForestRegression", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
702
PipelineNode node = new PipelineNode("FastForestBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
722
PipelineNode node = new PipelineNode("FastForestBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
740
PipelineNode node = new PipelineNode("AveragedPerceptronBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
760
PipelineNode node = new PipelineNode("AveragedPerceptronBinary", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);
775
PipelineNode node = new PipelineNode("ImageClassification", PipelineNodeType.
Trainer
, default(string[]), default(string), elementProperties);