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Fix entry point name for Logistic Regression (LogisticRegressor is misleading) #139

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May 14, 2018
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Fix entry point name for Logistic Regression (LogisticRegressor is misleading) #139

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4d30b9a
Fix name for Logistic Regression
May 13, 2018
0537e87
Adding the updated CSharpAPI.cs with LR name fix
May 13, 2018
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4 changes: 2 additions & 2 deletions ZBaselines/Common/EntryPoints/core_ep-list.tsv
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Expand Up @@ -23,7 +23,6 @@ Models.Summarizer Summarize a linear regression predictor. Microsoft.ML.Runtime.
Models.TrainTestBinaryEvaluator Train test for binary classification Microsoft.ML.Runtime.EntryPoints.TrainTestBinaryMacro TrainTestBinary Microsoft.ML.Runtime.EntryPoints.TrainTestBinaryMacro+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.TrainTestBinaryMacro+Output]
Models.TrainTestEvaluator General train test for any supported evaluator Microsoft.ML.Runtime.EntryPoints.TrainTestMacro TrainTest Microsoft.ML.Runtime.EntryPoints.TrainTestMacro+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.Runtime.EntryPoints.TrainTestMacro+Output]
Trainers.AveragedPerceptronBinaryClassifier Train a Average perceptron. Microsoft.ML.Runtime.Learners.AveragedPerceptronTrainer TrainBinary Microsoft.ML.Runtime.Learners.AveragedPerceptronTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Trainers.BinaryLogisticRegressor Train a logistic regression binary model Microsoft.ML.Runtime.Learners.LogisticRegression TrainBinary Microsoft.ML.Runtime.Learners.LogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Trainers.FastForestBinaryClassifier Uses a random forest learner to perform binary classification. Microsoft.ML.Runtime.FastTree.FastForest TrainBinary Microsoft.ML.Runtime.FastTree.FastForestClassification+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Trainers.FastForestRegressor Trains a random forest to fit target values using least-squares. Microsoft.ML.Runtime.FastTree.FastForest TrainRegression Microsoft.ML.Runtime.FastTree.FastForestRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput
Trainers.FastTreeBinaryClassifier Uses a logit-boost boosted tree learner to perform binary classification. Microsoft.ML.Runtime.FastTree.FastTree TrainBinary Microsoft.ML.Runtime.FastTree.FastTreeBinaryClassificationTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Expand All @@ -34,7 +33,8 @@ Trainers.GeneralizedAdditiveModelBinaryClassifier Trains a gradient boosted stum
Trainers.GeneralizedAdditiveModelRegressor Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features. Microsoft.ML.Runtime.FastTree.Gam TrainRegression Microsoft.ML.Runtime.FastTree.RegressionGamTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput
Trainers.KMeansPlusPlusClusterer K-means is a popular clustering algorithm. With K-means, the data is clustered into a specified number of clusters in order to minimize the within-cluster sum of squares. K-means++ improves upon K-means by using a better method for choosing the initial cluster centers. Microsoft.ML.Runtime.KMeans.KMeansPlusPlusTrainer TrainKMeans Microsoft.ML.Runtime.KMeans.KMeansPlusPlusTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+ClusteringOutput
Trainers.LinearSvmBinaryClassifier Train a linear SVM. Microsoft.ML.Runtime.Learners.LinearSvm TrainLinearSvm Microsoft.ML.Runtime.Learners.LinearSvm+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Trainers.LogisticRegressor Train a logistic regression multi class model Microsoft.ML.Runtime.Learners.LogisticRegression TrainMultiClass Microsoft.ML.Runtime.Learners.MulticlassLogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput
Trainers.LogisticRegressionBinaryClassifier Train a logistic regression binary model Microsoft.ML.Runtime.Learners.LogisticRegression TrainBinary Microsoft.ML.Runtime.Learners.LogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+BinaryClassificationOutput
Trainers.LogisticRegressionClassifier Train a logistic regression multi class model Microsoft.ML.Runtime.Learners.LogisticRegression TrainMultiClass Microsoft.ML.Runtime.Learners.MulticlassLogisticRegression+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput
Trainers.NaiveBayesClassifier Train a MultiClassNaiveBayesTrainer. Microsoft.ML.Runtime.Learners.MultiClassNaiveBayesTrainer TrainMultiClassNaiveBayesTrainer Microsoft.ML.Runtime.Learners.MultiClassNaiveBayesTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+MulticlassClassificationOutput
Trainers.OnlineGradientDescentRegressor Train a Online gradient descent perceptron. Microsoft.ML.Runtime.Learners.OnlineGradientDescentTrainer TrainRegression Microsoft.ML.Runtime.Learners.OnlineGradientDescentTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput
Trainers.OrdinaryLeastSquaresRegressor Train an OLS regression model. Microsoft.ML.Runtime.Learners.OlsLinearRegressionTrainer TrainRegression Microsoft.ML.Runtime.Learners.OlsLinearRegressionTrainer+Arguments Microsoft.ML.Runtime.EntryPoints.CommonOutputs+RegressionOutput
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