added catalog extensions and moved tensorflow arguments

src/Microsoft.ML.StandardLearners/Standard/Simple/SimpleTrainers.cs

@@ -234,7 +234,7 @@ private void MapDist(in VBuffer<float> src, ref float score, ref float prob)
     }
 
     /// <summary>
-    /// Learns the prior distribution for 0/1 class labels and just outputs that.
+    /// Learns the prior distribution for 0/1 class labels and outputs that.
     /// </summary>
     public sealed class PriorTrainer : TrainerBase<PriorModelParameters>,
         ITrainerEstimator<BinaryPredictionTransformer<PriorModelParameters>, PriorModelParameters>
@@ -263,8 +263,8 @@ internal PriorTrainer(IHostEnvironment env, Options options)
         /// <summary>
         /// Initializes PriorTrainer object.
         /// </summary>
-        internal PriorTrainer(IHost host, String labelColumn, String weightColunn = null)
-            : base(host, LoadNameValue)
+        internal PriorTrainer(IHostEnvironment env, String labelColumn, String weightColunn = null)
+            : base(env, LoadNameValue)
         {
             Contracts.CheckValue(labelColumn, nameof(labelColumn));
             Contracts.CheckValueOrNull(weightColunn);

src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs

@@ -558,28 +558,27 @@ public static LinearSvmTrainer LinearSupportVectorMachines(this BinaryClassifica
         }
 
         /// <summary>
-        /// Predict a target using a linear binary classification model trained with the <see cref="LinearSvmTrainer"/> trainer.
+        /// Predict a target using a random binary classification model <see cref="RandomTrainer"/>.
         /// </summary>
-        /// <remarks>
-        /// <para>
-        /// The idea behind support vector machines, is to map instances into a high dimensional space
-        /// in which the two classes are linearly separable, i.e., there exists a hyperplane such that all the positive examples are on one side of it,
-        /// and all the negative examples are on the other.
-        /// </para>
-        /// <para>
-        /// After this mapping, quadratic programming is used to find the separating hyperplane that maximizes the
-        /// margin, i.e., the minimal distance between it and the instances.
-        /// </para>
-        /// </remarks>
         /// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
-        /// <param name="options">Advanced arguments to the algorithm.</param>
-        public static LinearSvmTrainer LinearSupportVectorMachines(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
-            LinearSvmTrainer.Options options)
+        public static RandomTrainer Random(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog)
         {
             Contracts.CheckValue(catalog, nameof(catalog));
-            Contracts.CheckValue(options, nameof(options));
+            return new RandomTrainer(CatalogUtils.GetEnvironment(catalog), new RandomTrainer.Options());
+        }
 
-            return new LinearSvmTrainer(CatalogUtils.GetEnvironment(catalog), options);
+        /// <summary>
+        /// Predict a target using a binary classification model trained with <see cref="PriorTrainer"/> trainer.
+        /// </summary>
+        /// <param name="catalog">The <see cref="BinaryClassificationCatalog"/>.</param>
+        /// <param name="labelColumn">The name of the label column. </param>
+        /// <param name="weightsColumn">The optional name of the weights column.</param>
+        public static PriorTrainer Prior(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
+            string labelColumn = DefaultColumnNames.Label,
+            string weightsColumn = null)
+        {
+            Contracts.CheckValue(catalog, nameof(catalog));
+            return new PriorTrainer(CatalogUtils.GetEnvironment(catalog), labelColumn, weightsColumn);
         }
     }
 }

src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs

@@ -85,23 +85,23 @@ public static TensorFlowEstimator ScoreTensorFlowModel(this TransformsCatalog ca
             => new TensorFlowEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnNames, inputColumnNames, tensorFlowModel);
 
         /// <summary>
-        /// Score or Retrain a tensorflow model (based on setting of the <see cref="TensorFlowTransformer.Options.ReTrain"/>) setting.
-        /// The model is specified in the <see cref="TensorFlowTransformer.Options.ModelLocation"/>.
+        /// Score or Retrain a tensorflow model (based on setting of the <see cref="TensorFlowEstimator.Options.ReTrain"/>) setting.
+        /// The model is specified in the <see cref="TensorFlowEstimator.Options.ModelLocation"/>.
         /// </summary>
         /// <param name="catalog">The transform's catalog.</param>
-        /// <param name="options">The <see cref="TensorFlowTransformer.Options"/> specifying the inputs and the settings of the <see cref="TensorFlowEstimator"/>.</param>
+        /// <param name="options">The <see cref="TensorFlowEstimator.Options"/> specifying the inputs and the settings of the <see cref="TensorFlowEstimator"/>.</param>
         public static TensorFlowEstimator TensorFlow(this TransformsCatalog catalog,
-            TensorFlowTransformer.Options options)
+            TensorFlowEstimator.Options options)
             => new TensorFlowEstimator(CatalogUtils.GetEnvironment(catalog), options);
 
         /// <summary>
-        /// Scores or retrains (based on setting of the <see cref="TensorFlowTransformer.Options.ReTrain"/>) a pre-traiend TensorFlow model specified via <paramref name="tensorFlowModel"/>.
+        /// Scores or retrains (based on setting of the <see cref="TensorFlowEstimator.Options.ReTrain"/>) a pre-traiend TensorFlow model specified via <paramref name="tensorFlowModel"/>.
         /// </summary>
         /// <param name="catalog">The transform's catalog.</param>
-        /// <param name="options">The <see cref="TensorFlowTransformer.Options"/> specifying the inputs and the settings of the <see cref="TensorFlowEstimator"/>.</param>
+        /// <param name="options">The <see cref="TensorFlowEstimator.Options"/> specifying the inputs and the settings of the <see cref="TensorFlowEstimator"/>.</param>
         /// <param name="tensorFlowModel">The pre-loaded TensorFlow model.</param>
         public static TensorFlowEstimator TensorFlow(this TransformsCatalog catalog,
-            TensorFlowTransformer.Options options,
+            TensorFlowEstimator.Options options,
             TensorFlowModelInfo tensorFlowModel)
             => new TensorFlowEstimator(CatalogUtils.GetEnvironment(catalog), options, tensorFlowModel);
     }