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);
}