public void Test_Ranking_MSLRWeb10K_RawNumericFeatures_FastTreeRanking() { // This benchmark is profiling bulk scoring speed and not training speed. string cmd = @"Test data=" + _mslrWeb10kTest + " in=" + _modelPathMslr; var environment = EnvironmentFactory.CreateRankingEnvironment <RankingEvaluator, TextLoader, HashingTransformer, FastTreeRankingTrainer, FastTreeRankingModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void Test_Multiclass_WikiDetox_BigramsAndTrichar_OVAAveragedPerceptron() { // This benchmark is profiling bulk scoring speed and not training speed. string modelpath = Path.Combine(Path.GetDirectoryName(typeof(MulticlassClassificationTest).Assembly.Location), @"WikiModel.fold000.zip"); string cmd = @"Test data=" + _dataPathWiki + " in=" + modelpath; var environment = EnvironmentFactory.CreateClassificationEnvironment <TextLoader, OneHotEncodingTransformer, AveragedPerceptronTrainer, LinearBinaryModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void TrainTest_Ranking_MSLRWeb10K_RawNumericFeatures_FastTreeRanking() { string cmd = @"TrainTest test=" + _mslrWeb10kValidate + " eval=RankingEvaluator{t=10}" + " data=" + _mslrWeb10kTrain + " loader=TextLoader{col=Label:R4:0 col=GroupId:TX:1 col=Features:R4:2-138}" + " xf=HashTransform{col=GroupId} xf=NAHandleTransform{col=Features}" + " tr=FastTreeRanking{}"; var environment = EnvironmentFactory.CreateRankingEnvironment <RankingEvaluator, TextLoader, HashingTransformer, FastTreeRankingTrainer, FastTreeRankingModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void CV_Multiclass_WikiDetox_BigramsAndTrichar_LightGBMMulticlass() { string cmd = @"CV k=5 data=" + _dataPathWiki + " loader=TextLoader{quote=- sparse=- col=Label:R4:0 col=rev_id:TX:1 col=comment:TX:2 col=logged_in:BL:4 col=ns:TX:5 col=sample:TX:6 col=split:TX:7 col=year:R4:3 header=+}" + " xf=Convert{col=logged_in type=R4}" + " xf=CategoricalTransform{col=ns}" + " xf=TextTransform{col=FeaturesText:comment wordExtractor=NGramExtractorTransform{ngram=2}}" + " xf=Concat{col=Features:FeaturesText,logged_in,ns}" + " tr=LightGBMMulticlass{iter=10}"; var environment = EnvironmentFactory.CreateClassificationEnvironment <TextLoader, OneHotEncodingTransformer, LightGbmMulticlassTrainer, OneVersusAllModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void CV_Multiclass_WikiDetox_WordEmbeddings_SDCAMC() { string cmd = @"CV k=5 data=" + _dataPathWiki + " tr=SDCAMC" + " loader=TextLoader{quote=- sparse=- col=Label:R4:0 col=rev_id:TX:1 col=comment:TX:2 col=logged_in:BL:4 col=ns:TX:5 col=sample:TX:6 col=split:TX:7 col=year:R4:3 header=+}" + " xf=Convert{col=logged_in type=R4}" + " xf=CategoricalTransform{col=ns}" + " xf=TextTransform{col=FeaturesText:comment tokens=+ wordExtractor={} charExtractor={}}" + " xf=WordEmbeddingsTransform{col=FeaturesWordEmbedding:FeaturesText_TransformedText model=FastTextWikipedia300D}" + " xf=Concat{col=Features:FeaturesWordEmbedding,logged_in,ns}"; var environment = EnvironmentFactory.CreateClassificationEnvironment <TextLoader, OneHotEncodingTransformer, SdcaMaximumEntropyMulticlassTrainer, MaximumEntropyModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void SetupScoringSpeedTests() { _dataPathWiki = GetBenchmarkDataPathAndEnsureData(TestDatasets.WikiDetox.trainFilename, TestDatasets.WikiDetox.path); if (!File.Exists(_dataPathWiki)) { throw new FileNotFoundException(string.Format(Errors.DatasetNotFound, _dataPathWiki)); } _modelPathWiki = Path.Combine(Path.GetDirectoryName(typeof(MulticlassClassificationTest).Assembly.Location), @"WikiModel.zip"); string cmd = @"CV k=5 data=" + _dataPathWiki + " loader=TextLoader{quote=- sparse=- col=Label:R4:0 col=rev_id:TX:1 col=comment:TX:2 col=logged_in:BL:4 col=ns:TX:5 col=sample:TX:6 col=split:TX:7 col=year:R4:3 header=+} xf=Convert{col=logged_in type=R4}" + " xf=CategoricalTransform{col=ns}" + " xf=TextTransform{col=FeaturesText:comment wordExtractor=NGramExtractorTransform{ngram=2}}" + " xf=Concat{col=Features:FeaturesText,logged_in,ns}" + " tr=OVA{p=AveragedPerceptron{iter=10}}" + " out={" + _modelPathWiki + "}"; var environment = EnvironmentFactory.CreateClassificationEnvironment <TextLoader, OneHotEncodingTransformer, AveragedPerceptronTrainer, LinearBinaryModelParameters>(); cmd.ExecuteMamlCommand(environment); }
public void SetupScoringSpeedTests() { _mslrWeb10kTest = GetBenchmarkDataPathAndEnsureData(TestDatasets.MSLRWeb.testFilename, TestDatasets.MSLRWeb.path); _mslrWeb10kValidate = GetBenchmarkDataPathAndEnsureData(TestDatasets.MSLRWeb.validFilename, TestDatasets.MSLRWeb.path); _mslrWeb10kTrain = GetBenchmarkDataPathAndEnsureData(TestDatasets.MSLRWeb.trainFilename, TestDatasets.MSLRWeb.path); if (!File.Exists(_mslrWeb10kTest)) { throw new FileNotFoundException(string.Format(Errors.DatasetNotFound, _mslrWeb10kTest)); } if (!File.Exists(_mslrWeb10kValidate)) { throw new FileNotFoundException(string.Format(Errors.DatasetNotFound, _mslrWeb10kValidate)); } if (!File.Exists(_mslrWeb10kTrain)) { throw new FileNotFoundException(string.Format(Errors.DatasetNotFound, _mslrWeb10kTrain)); } _modelPathMslr = Path.Combine(Path.GetDirectoryName(typeof(RankingTest).Assembly.Location), "FastTreeRankingModel.zip"); string cmd = @"TrainTest test=" + _mslrWeb10kValidate + " eval=RankingEvaluator{t=10}" + " data=" + _mslrWeb10kTrain + " loader=TextLoader{col=Label:R4:0 col=GroupId:TX:1 col=Features:R4:2-138}" + " xf=HashTransform{col=GroupId}" + " xf=NAHandleTransform{col=Features}" + " tr=FastTreeRanking{}" + " out={" + _modelPathMslr + "}"; var environment = EnvironmentFactory.CreateRankingEnvironment <RankingEvaluator, TextLoader, HashingTransformer, FastTreeRankingTrainer, FastTreeRankingModelParameters>(); cmd.ExecuteMamlCommand(environment); }