143 references to TrainerName
Microsoft.ML.AutoML (87)
API\ExperimentBase.cs (2)
29
private readonly IEnumerable<
TrainerName
> _trainerAllowList;
36
IEnumerable<
TrainerName
> trainerAllowList)
Experiment\Experiment.cs (2)
24
private readonly IEnumerable<
TrainerName
> _trainerAllowList;
46
IEnumerable<
TrainerName
> trainerAllowList,
Experiment\RecipeInference.cs (1)
16
ColumnInformation columnInfo, IEnumerable<
TrainerName
> trainerAllowList)
Experiment\SuggestedPipeline.cs (3)
86
var
trainerName = (
TrainerName
)Enum.Parse(typeof(
TrainerName
), pipelineNode.Name);
Experiment\SuggestedTrainer.cs (1)
14
public
TrainerName
TrainerName { get; }
PipelineSuggesters\PipelineSuggester.cs (2)
36
IEnumerable<
TrainerName
> trainerAllowList = null)
113
var selectedTrainerNames = new HashSet<
TrainerName
>(selectedTrainers.Select(t => t.TrainerName));
TrainerExtensions\TrainerExtensionCatalog.cs (38)
13
private static readonly IDictionary<
TrainerName
, Type> _trainerNamesToExtensionTypes =
14
new Dictionary<
TrainerName
, Type>()
16
{
TrainerName
.AveragedPerceptronBinary, typeof(AveragedPerceptronBinaryExtension) },
17
{
TrainerName
.AveragedPerceptronOva, typeof(AveragedPerceptronOvaExtension) },
18
{
TrainerName
.FastForestBinary, typeof(FastForestBinaryExtension) },
19
{
TrainerName
.FastForestOva, typeof(FastForestOvaExtension) },
20
{
TrainerName
.FastForestRegression, typeof(FastForestRegressionExtension) },
21
{
TrainerName
.FastTreeBinary, typeof(FastTreeBinaryExtension) },
22
{
TrainerName
.FastTreeOva, typeof(FastTreeOvaExtension) },
23
{
TrainerName
.FastTreeRegression, typeof(FastTreeRegressionExtension) },
24
{
TrainerName
.FastTreeTweedieRegression, typeof(FastTreeTweedieRegressionExtension) },
25
{
TrainerName
.LightGbmBinary, typeof(LightGbmBinaryExtension) },
26
{
TrainerName
.LightGbmMulti, typeof(LightGbmMultiExtension) },
27
{
TrainerName
.LightGbmRegression, typeof(LightGbmRegressionExtension) },
28
{
TrainerName
.LinearSvmBinary, typeof(LinearSvmBinaryExtension) },
29
{
TrainerName
.LinearSvmOva, typeof(LinearSvmOvaExtension) },
30
{
TrainerName
.LbfgsLogisticRegressionBinary, typeof(LbfgsLogisticRegressionBinaryExtension) },
31
{
TrainerName
.LbfgsMaximumEntropyMulti, typeof(LbfgsMaximumEntropyMultiExtension) },
32
{
TrainerName
.LbfgsLogisticRegressionOva, typeof(LbfgsLogisticRegressionOvaExtension) },
33
{
TrainerName
.OnlineGradientDescentRegression, typeof(OnlineGradientDescentRegressionExtension) },
34
{
TrainerName
.OlsRegression, typeof(OlsRegressionExtension) },
35
{
TrainerName
.LbfgsPoissonRegression, typeof(LbfgsPoissonRegressionExtension) },
36
{
TrainerName
.SdcaLogisticRegressionBinary, typeof(SdcaLogisticRegressionBinaryExtension) },
37
{
TrainerName
.SdcaMaximumEntropyMulti, typeof(SdcaMaximumEntropyMultiExtension) },
38
{
TrainerName
.SdcaRegression, typeof(SdcaRegressionExtension) },
39
{
TrainerName
.SgdCalibratedBinary, typeof(SgdCalibratedBinaryExtension) },
40
{
TrainerName
.SgdCalibratedOva, typeof(SgdCalibratedOvaExtension) },
41
{
TrainerName
.SymbolicSgdLogisticRegressionBinary, typeof(SymbolicSgdLogisticRegressionBinaryExtension) },
42
{
TrainerName
.SymbolicSgdLogisticRegressionOva, typeof(SymbolicSgdLogisticRegressionOvaExtension) },
43
{
TrainerName
.MatrixFactorization, typeof(MatrixFactorizationExtension) },
44
{
TrainerName
.ImageClassification, typeof(ImageClassificationExtension) },
45
{
TrainerName
.LightGbmRanking, typeof(LightGbmRankingExtension) },
46
{
TrainerName
.FastTreeRanking, typeof(FastTreeRankingExtension) },
49
private static readonly IDictionary<Type,
TrainerName
> _extensionTypesToTrainerNames =
52
public static
TrainerName
GetTrainerName(ITrainerExtension trainerExtension)
57
public static ITrainerExtension GetTrainerExtension(
TrainerName
trainerName)
64
IEnumerable<
TrainerName
> allowList, ColumnInformation columnInfo)
106
allowList = new HashSet<
TrainerName
>(allowList);
TrainerExtensions\TrainerExtensionUtil.cs (38)
105
Name =
TrainerName
.Ova.ToString(),
117
public static PipelineNode BuildPipelineNode(
TrainerName
trainerName, IEnumerable<SweepableParam> sweepParams,
134
public static PipelineNode BuildLightGbmPipelineNode(
TrainerName
trainerName, IEnumerable<SweepableParam> sweepParams,
193
public static ParameterSet BuildParameterSet(
TrainerName
trainerName, IDictionary<string, object> props)
198
if (trainerName ==
TrainerName
.LightGbmBinary || trainerName ==
TrainerName
.LightGbmMulti ||
199
trainerName ==
TrainerName
.LightGbmRegression || trainerName ==
TrainerName
.LightGbmRanking)
301
public static
TrainerName
GetTrainerName(BinaryClassificationTrainer binaryTrainer)
306
return
TrainerName
.FastForestBinary;
308
return
TrainerName
.FastTreeBinary;
310
return
TrainerName
.LightGbmBinary;
312
return
TrainerName
.LbfgsLogisticRegressionBinary;
314
return
TrainerName
.SdcaLogisticRegressionBinary;
321
public static
TrainerName
GetTrainerName(MulticlassClassificationTrainer multiTrainer)
326
return
TrainerName
.FastForestOva;
328
return
TrainerName
.FastTreeOva;
330
return
TrainerName
.LightGbmMulti;
332
return
TrainerName
.LbfgsMaximumEntropyMulti;
334
return
TrainerName
.LbfgsLogisticRegressionOva;
336
return
TrainerName
.SdcaMaximumEntropyMulti;
343
public static
TrainerName
GetTrainerName(RegressionTrainer regressionTrainer)
348
return
TrainerName
.FastForestRegression;
350
return
TrainerName
.FastTreeRegression;
352
return
TrainerName
.FastTreeTweedieRegression;
354
return
TrainerName
.LightGbmRegression;
356
return
TrainerName
.LbfgsPoissonRegression;
358
return
TrainerName
.SdcaRegression;
365
public static
TrainerName
GetTrainerName(RankingTrainer rankingTrainer)
370
return
TrainerName
.FastTreeRanking;
372
return
TrainerName
.LightGbmRanking;
379
public static
TrainerName
GetTrainerName(RecommendationTrainer recommendationTrainer)
384
return
TrainerName
.MatrixFactorization;
391
public static IEnumerable<
TrainerName
> GetTrainerNames(IEnumerable<BinaryClassificationTrainer> binaryTrainers)
396
public static IEnumerable<
TrainerName
> GetTrainerNames(IEnumerable<MulticlassClassificationTrainer> multiTrainers)
401
public static IEnumerable<
TrainerName
> GetTrainerNames(IEnumerable<RegressionTrainer> regressionTrainers)
406
public static IEnumerable<
TrainerName
> GetTrainerNames(IEnumerable<RecommendationTrainer> recommendationTrainers)
411
public static IEnumerable<
TrainerName
> GetTrainerNames(IEnumerable<RankingTrainer> rankingTrainers)
Microsoft.ML.AutoML.Tests (13)
TrainerExtensionsTests.cs (13)
27
var trainerNames = Enum.GetValues(typeof(
TrainerName
)).Cast<
TrainerName
>()
28
.Except(new[] {
TrainerName
.Ova });
29
foreach (
var
trainerName in trainerNames)
34
if (trainerName !=
TrainerName
.ImageClassification)
56
var extension = TrainerExtensionCatalog.GetTrainerExtension(
TrainerName
.ImageClassification);
325
var binaryParams = TrainerExtensionUtil.BuildParameterSet(
TrainerName
.LightGbmBinary, props);
326
var multiParams = TrainerExtensionUtil.BuildParameterSet(
TrainerName
.LightGbmMulti, props);
327
var regressionParams = TrainerExtensionUtil.BuildParameterSet(
TrainerName
.LightGbmRegression, props);
328
var rankingParams = TrainerExtensionUtil.BuildParameterSet(
TrainerName
.LightGbmRanking, props);
348
var sdcaParams = TrainerExtensionUtil.BuildParameterSet(
TrainerName
.SdcaLogisticRegressionBinary, props);
411
var allowList = new[] {
TrainerName
.AveragedPerceptronBinary,
TrainerName
.FastForestBinary };
Microsoft.ML.CodeGenerator (41)
CodeGenerator\CSharp\CodeGenerator.cs (15)
27
private static readonly HashSet<string> _recommendationTrainers = new HashSet<string>() {
TrainerName
.MatrixFactorization.ToString() };
28
private static readonly HashSet<string> _lightGbmTrainers = new HashSet<string>() {
TrainerName
.LightGbmBinary.ToString(),
TrainerName
.LightGbmMulti.ToString(),
29
TrainerName
.LightGbmRegression.ToString(),
TrainerName
.LightGbmRanking.ToString() };
30
private static readonly HashSet<string> _mklComponentsTrainers = new HashSet<string>() {
TrainerName
.OlsRegression.ToString(),
TrainerName
.SymbolicSgdLogisticRegressionBinary.ToString() };
31
private static readonly HashSet<string> _fastTreeTrainers = new HashSet<string>() {
TrainerName
.FastForestBinary.ToString(),
TrainerName
.FastForestRegression.ToString(),
32
TrainerName
.FastTreeBinary.ToString(),
TrainerName
.FastTreeRegression.ToString(),
TrainerName
.FastTreeTweedieRegression.ToString(),
TrainerName
.FastTreeRanking.ToString() };
34
private static readonly HashSet<string> _imageClassificationTrainers = new HashSet<string>() {
TrainerName
.ImageClassification.ToString() };
106
if (currentNode.Name ==
TrainerName
.Ova.ToString())
CodeGenerator\CSharp\TrainerGeneratorFactory.cs (26)
22
if (Enum.TryParse(node.Name, out
TrainerName
trainer))
26
case
TrainerName
.LightGbmBinary:
28
case
TrainerName
.LightGbmMulti:
30
case
TrainerName
.LightGbmRegression:
32
case
TrainerName
.AveragedPerceptronBinary:
34
case
TrainerName
.FastForestBinary:
36
case
TrainerName
.FastForestRegression:
38
case
TrainerName
.FastTreeBinary:
40
case
TrainerName
.FastTreeRegression:
42
case
TrainerName
.FastTreeTweedieRegression:
44
case
TrainerName
.LinearSvmBinary:
46
case
TrainerName
.LbfgsLogisticRegressionBinary:
48
case
TrainerName
.LbfgsMaximumEntropyMulti:
50
case
TrainerName
.OnlineGradientDescentRegression:
52
case
TrainerName
.OlsRegression:
54
case
TrainerName
.LbfgsPoissonRegression:
56
case
TrainerName
.SdcaLogisticRegressionBinary:
58
case
TrainerName
.SdcaMaximumEntropyMulti:
60
case
TrainerName
.SdcaRegression:
62
case
TrainerName
.SgdCalibratedBinary:
64
case
TrainerName
.SymbolicSgdLogisticRegressionBinary:
66
case
TrainerName
.Ova:
68
case
TrainerName
.ImageClassification:
70
case
TrainerName
.MatrixFactorization:
72
case
TrainerName
.LightGbmRanking:
74
case
TrainerName
.FastTreeRanking:
Microsoft.ML.CodeGenerator.Tests (2)
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);