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file name should be vanilla
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‎src/Microsoft.ML.FastTree/FastTreeArguments.cs‎

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@@ -20,7 +20,7 @@ public interface IFastTreeTrainerFactory : IComponentFactory<ITrainer>
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{
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}
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/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastTree"]/*' />
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/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
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public sealed partial class FastTreeBinaryClassificationTrainer
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{
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[TlcModule.Component(Name = LoadNameValue, FriendlyName = UserNameValue, Desc = Summary)]

‎src/Microsoft.ML.FastTree/FastTreeClassification.cs‎

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@@ -100,7 +100,7 @@ public static IPredictorProducing<Float> Create(IHostEnvironment env, ModelLoadC
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public override PredictionKind PredictionKind { get { return PredictionKind.BinaryClassification; } }
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}
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/// <include file = './XMLDoc.xml' path='docs/members/member[@name="FastTree"]/*' />
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/// <include file = './doc.xml' path='docs/members/member[@name="FastTree"]/*' />
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public sealed partial class FastTreeBinaryClassificationTrainer :
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BoostingFastTreeTrainerBase<FastTreeBinaryClassificationTrainer.Arguments, IPredictorWithFeatureWeights<Float>>
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{
@@ -346,7 +346,7 @@ public static partial class FastTree
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Desc = FastTreeBinaryClassificationTrainer.Summary,
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UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
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ShortName = FastTreeBinaryClassificationTrainer.ShortName,
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeRanking.cs‎

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@@ -38,7 +38,7 @@
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namespace Microsoft.ML.Runtime.FastTree
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{
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/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastTree"]/*' />
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/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
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public sealed partial class FastTreeRankingTrainer : BoostingFastTreeTrainerBase<FastTreeRankingTrainer.Arguments, FastTreeRankingPredictor>,
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IHasLabelGains
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{
@@ -1101,7 +1101,7 @@ public static partial class FastTree
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Desc = FastTreeRankingTrainer.Summary,
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UserName = FastTreeRankingTrainer.UserNameValue,
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ShortName = FastTreeRankingTrainer.ShortName,
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeRegression.cs‎

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@@ -31,7 +31,7 @@
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namespace Microsoft.ML.Runtime.FastTree
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{
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/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastTree"]/*' />
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/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
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public sealed partial class FastTreeRegressionTrainer : BoostingFastTreeTrainerBase<FastTreeRegressionTrainer.Arguments, FastTreeRegressionPredictor>
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{
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public const string LoadNameValue = "FastTreeRegression";
@@ -453,7 +453,7 @@ public static partial class FastTree
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Desc = FastTreeRegressionTrainer.Summary,
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UserName = FastTreeRegressionTrainer.UserNameValue,
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ShortName = FastTreeRegressionTrainer.ShortName,
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
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public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeTweedie.cs‎

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@@ -30,7 +30,7 @@ namespace Microsoft.ML.Runtime.FastTree
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// The Tweedie boosting model follows the mathematics established in:
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// Yang, Quan, and Zou. "Insurance Premium Prediction via Gradient Tree-Boosted Tweedie Compound Poisson Models."
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// https://arxiv.org/pdf/1508.06378.pdf
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/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastTreeTweedieRegression"]/*' />
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/// <include file='./doc.xml' path='docs/members/member[@name="FastTreeTweedieRegression"]/*' />
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public sealed partial class FastTreeTweedieTrainer : BoostingFastTreeTrainerBase<FastTreeTweedieTrainer.Arguments, FastTreeTweediePredictor>
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{
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public const string LoadNameValue = "FastTreeTweedieRegression";
@@ -461,7 +461,7 @@ public static partial class FastTree
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Desc = FastTreeTweedieTrainer.Summary,
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UserName = FastTreeTweedieTrainer.UserNameValue,
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ShortName = FastTreeTweedieTrainer.ShortName,
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XmlInclude = new [] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastTreeTweedieRegression""]/*' />" })]
464+
XmlInclude = new [] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTreeTweedieRegression""]/*' />" })]
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public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/RandomForestClassification.cs‎

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@@ -106,7 +106,7 @@ public static IPredictorProducing<Float> Create(IHostEnvironment env, ModelLoadC
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}
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}
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109-
/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastForest"]/*' />
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/// <include file='./doc.xml' path='docs/members/member[@name="FastForest"]/*' />
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public sealed partial class FastForestClassification :
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RandomForestTrainerBase<FastForestClassification.Arguments, IPredictorWithFeatureWeights<Float>>
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{
@@ -213,7 +213,7 @@ public static partial class FastForest
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Desc = FastForestClassification.Summary,
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UserName = FastForestClassification.UserNameValue,
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ShortName = FastForestClassification.ShortName,
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
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XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
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public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/RandomForestRegression.cs‎

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@@ -137,7 +137,7 @@ public ISchemaBindableMapper CreateMapper(Double[] quantiles)
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}
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}
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/// <include file='./XMLDoc.xml' path='docs/members/member[@name="FastForest"]/*' />
140+
/// <include file='./doc.xml' path='docs/members/member[@name="FastForest"]/*' />
141141
public sealed partial class FastForestRegression : RandomForestTrainerBase<FastForestRegression.Arguments, FastForestRegressionPredictor>
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{
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public sealed class Arguments : FastForestArgumentsBase
@@ -285,7 +285,7 @@ public static partial class FastForest
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Desc = FastForestRegression.Summary,
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UserName = FastForestRegression.LoadNameValue,
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ShortName = FastForestRegression.ShortName,
288-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/XMLDoc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
288+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
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public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/XMLDoc.xml‎ renamed to ‎src/Microsoft.ML.FastTree/doc.xml‎

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@@ -8,7 +8,7 @@
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</summary>
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<remarks>
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<para>
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FastTrees is an efficient implementation of the <a href='https://arxiv.org/abs/1505.01866'>MART</a> gradient boosting algorithm.
11+
FastTree is an efficient implementation of the <a href='https://arxiv.org/abs/1505.01866'>MART</a> gradient boosting algorithm.
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Gradient boosting is a machine learning technique for regression problems.
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It builds each regression tree in a step-wise fashion, using a predefined loss function to measure the error for each step and corrects for it in the next.
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So this prediction model is actually an ensemble of weaker prediction models. In regression problems, boosting builds a series of of such trees in a step-wise fashion and then selects the optimal tree using an arbitrary differentiable loss function.

‎src/Microsoft.ML.KMeansClustering/KMeansPlusPlusTrainer.cs‎

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@@ -28,7 +28,7 @@
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namespace Microsoft.ML.Runtime.KMeans
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{
31-
/// <include file='./XMLDoc.xml' path='docs/members/member[@name="KMeans++"]/*' />
31+
/// <include file='./doc.xml' path='docs/members/member[@name="KMeans++"]/*' />
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public class KMeansPlusPlusTrainer : TrainerBase<RoleMappedData, KMeansPredictor>
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{
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public const string LoadNameValue = "KMeansPlusPlus";
@@ -213,7 +213,7 @@ private static int ComputeNumThreads(IHost host, int? argNumThreads)
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Desc = Summary,
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UserName = UserNameValue,
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ShortName = ShortName,
216-
XmlInclude = new[] { @"<include file='../Microsoft.ML.KMeansClustering/XMLDoc.xml' path='docs/members/member[@name=""KMeans++""]/*' />" })]
216+
XmlInclude = new[] { @"<include file='../Microsoft.ML.KMeansClustering/doc.xml' path='docs/members/member[@name=""KMeans++""]/*' />" })]
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public static CommonOutputs.ClusteringOutput TrainKMeans(IHostEnvironment env, Arguments input)
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{
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Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.KMeansClustering/XMLDoc.xml‎ renamed to ‎src/Microsoft.ML.KMeansClustering/doc.xml‎

File renamed without changes.

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