From ff4cd97360240ab623a5349d0b14a1563694e4c0 Mon Sep 17 00:00:00 2001 From: Artidoro Pagnoni Date: Tue, 12 Feb 2019 16:30:08 -0800 Subject: [PATCH] adding references to samples and regenerating catalog --- .../StandardLearnersCatalog.cs | 12 ++++++++++++ .../Common/EntryPoints/core_ep-list.tsv | 4 ++-- 2 files changed, 14 insertions(+), 2 deletions(-) diff --git a/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs b/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs index 1d83039e196..6c4d674d7f0 100644 --- a/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs +++ b/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs @@ -564,6 +564,12 @@ public static LinearSvmTrainer LinearSupportVectorMachines(this BinaryClassifica /// This trainer can be used as a baseline for other more sophisticated mdels. /// /// The . + /// + /// + /// + /// public static RandomTrainer Random(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog) { Contracts.CheckValue(catalog, nameof(catalog)); @@ -580,6 +586,12 @@ public static RandomTrainer Random(this BinaryClassificationCatalog.BinaryClassi /// The . /// The name of the label column. /// The optional name of the weights column. + /// + /// + /// + /// public static PriorTrainer Prior(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog, string labelColumn = DefaultColumnNames.Label, string weightsColumn = null) diff --git a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv index 0c60d474be0..34822a5f0ff 100644 --- a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv +++ b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv @@ -60,7 +60,7 @@ Trainers.LightGbmRegressor LightGBM Regression Microsoft.ML.LightGBM.LightGbm Tr Trainers.LinearSvmBinaryClassifier Train a linear SVM. Microsoft.ML.Trainers.Online.LinearSvmTrainer TrainLinearSvm Microsoft.ML.Trainers.Online.LinearSvmTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput Trainers.LogisticRegressionBinaryClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Trainers.LogisticRegression TrainBinary Microsoft.ML.Trainers.LogisticRegression+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput Trainers.LogisticRegressionClassifier Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function. Microsoft.ML.Trainers.LogisticRegression TrainMultiClass Microsoft.ML.Trainers.MulticlassLogisticRegression+Options Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.NaiveBayesClassifier Train a MultiClassNaiveBayesTrainer. Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer TrainMultiClassNaiveBayesTrainer Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.NaiveBayesClassifier Train a MultiClassNaiveBayesTrainer. Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer TrainMultiClassNaiveBayesTrainer Microsoft.ML.Trainers.MultiClassNaiveBayesTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput Trainers.OnlineGradientDescentRegressor Train a Online gradient descent perceptron. Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer TrainRegression Microsoft.ML.Trainers.Online.OnlineGradientDescentTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.OrdinaryLeastSquaresRegressor Train an OLS regression model. Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer TrainRegression Microsoft.ML.Trainers.HalLearners.OlsLinearRegressionTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.PcaAnomalyDetector Train an PCA Anomaly model. Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer TrainPcaAnomaly Microsoft.ML.Trainers.PCA.RandomizedPcaTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+AnomalyDetectionOutput @@ -126,7 +126,7 @@ Transforms.ScoreColumnSelector Selects only the last score columns and the extra Transforms.Scorer Turn the predictor model into a transform model Microsoft.ML.EntryPoints.ScoreModel MakeScoringTransform Microsoft.ML.EntryPoints.ScoreModel+ModelInput Microsoft.ML.EntryPoints.ScoreModel+Output Transforms.Segregator Un-groups vector columns into sequences of rows, inverse of Group transform Microsoft.ML.Transforms.GroupingOperations Ungroup Microsoft.ML.Transforms.UngroupTransform+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput Transforms.SentimentAnalyzer Uses a pretrained sentiment model to score input strings Microsoft.ML.Transforms.Text.TextAnalytics AnalyzeSentiment Microsoft.ML.Transforms.Text.SentimentAnalyzingTransformer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -Transforms.TensorFlowScorer Transforms the data using the TensorFlow model. Microsoft.ML.Transforms.TensorFlowTransformer TensorFlowScorer Microsoft.ML.Transforms.TensorFlowTransformer+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +Transforms.TensorFlowScorer Transforms the data using the TensorFlow model. Microsoft.ML.Transforms.TensorFlowTransformer TensorFlowScorer Microsoft.ML.Transforms.TensorFlowEstimator+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput Transforms.TextFeaturizer A transform that turns a collection of text documents into numerical feature vectors. The feature vectors are normalized counts of (word and/or character) ngrams in a given tokenized text. Microsoft.ML.Transforms.Text.TextAnalytics TextTransform Microsoft.ML.Transforms.Text.TextFeaturizingEstimator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput Transforms.TextToKeyConverter Converts input values (words, numbers, etc.) to index in a dictionary. Microsoft.ML.Transforms.Categorical.Categorical TextToKey Microsoft.ML.Transforms.Conversions.ValueToKeyMappingTransformer+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput Transforms.TrainTestDatasetSplitter Split the dataset into train and test sets Microsoft.ML.EntryPoints.TrainTestSplit Split Microsoft.ML.EntryPoints.TrainTestSplit+Input Microsoft.ML.EntryPoints.TrainTestSplit+Output