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Adding documentation about the rest of the classes involved on generating the CSharpAPI (dotnet#529)
* Moving from xml strings to having the documentation details in xml files. For the summary text that is common between several learners, the examples will be added on a separate node. An example of how that will look like is in the LogisticRegressionBinaryClassifier and LogisticRegressionClassifier. * fixing the aftermath of renaming the XML file. * removing the Desc from the EntryPoint attribute is a bad idea. * removing the XML docs from the doc folder, and added them under the respective projects. * Some OS get picky about casing. * file name should be vanilla * Adding documentation for the first group of transforms * adding more documentation. changing the root of the XML documents from docs -> doc, since its only one. Switching all <see href /> to the valid <see cref /> * formatting tweaks, and adressing most of the code comments. * Extracted the examples outside of the member nodes in the xml, so that they only appear in the CSharpApi classes, and not on the runtime classes. * small fixes * addressing code comments * addressing Pete's comments. * Fixing language around the CharTokenizer description. Closes dotnet#389
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‎src/Microsoft.ML.Core/Utilities/ReservoirSampler.cs

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@@ -47,7 +47,7 @@ public interface IReservoirSampler<T>
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/// This class produces a sample without replacement from a stream of data of type <typeparamref name="T"/>.
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/// It is instantiated with a delegate that gets the next data point, and builds a reservoir in one pass by calling <see cref="Sample"/>
4949
/// for every data point in the stream. In case the next data point does not get 'picked' into the reservoir, the delegate is not invoked.
50-
/// Sampling is done according to the algorithm in this paper: <see href="http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53"/>.
50+
/// Sampling is done according to the algorithm in this paper: <a href="http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53">http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53</a>.
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/// </summary>
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public sealed class ReservoirSamplerWithoutReplacement<T> : IReservoirSampler<T>
5353
{
@@ -120,7 +120,7 @@ public IEnumerable<T> GetSample()
120120
/// This class produces a sample with replacement from a stream of data of type <typeparamref name="T"/>.
121121
/// It is instantiated with a delegate that gets the next data point, and builds a reservoir in one pass by calling <see cref="Sample"/>
122122
/// for every data point in the stream. In case the next data point does not get 'picked' into the reservoir, the delegate is not invoked.
123-
/// Sampling is done according to the algorithm in this paper: <see href="http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53"/>.
123+
/// Sampling is done according to the algorithm in this paper: <a href="http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53">http://epubs.siam.org/doi/pdf/10.1137/1.9781611972740.53</a>.
124124
/// </summary>
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public sealed class ReservoirSamplerWithReplacement<T> : IReservoirSampler<T>
126126
{

‎src/Microsoft.ML.Data/Evaluators/AucAggregator.cs

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@@ -408,7 +408,7 @@ public UnweightedAuPrcAggregator(IRandom rand, int reservoirSize)
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409409
/// <summary>
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/// Compute the AUPRC using the "lower trapesoid" estimator, as described in the paper
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/// <see href="http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf"/>.
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/// <a href="http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf">http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf</a>.
412412
/// </summary>
413413
protected override Double ComputeWeightedAuPrcCore(out Double unweighted)
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{
@@ -482,7 +482,7 @@ public WeightedAuPrcAggregator(IRandom rand, int reservoirSize)
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483483
/// <summary>
484484
/// Compute the AUPRC using the "lower trapesoid" estimator, as described in the paper
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/// <see href="http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf"/>.
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/// <a href="http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf">http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/aucpr_2013ecml_corrected.pdf</a>.
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/// </summary>
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protected override Double ComputeWeightedAuPrcCore(out Double unweighted)
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{

‎src/Microsoft.ML.Data/Transforms/NAFilter.cs

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@@ -26,6 +26,7 @@
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namespace Microsoft.ML.Runtime.Data
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{
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/// <include file='doc.xml' path='doc/members/member[@name="NAFilter"]'/>
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public sealed class NAFilter : FilterBase
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{
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private static class Defaults

‎src/Microsoft.ML.Data/Transforms/TermTransform.cs

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@@ -29,14 +29,14 @@
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namespace Microsoft.ML.Runtime.Data
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{
32-
/// <summary>
33-
/// TermTransform builds up term vocabularies (dictionaries).
34-
/// Notes:
35-
/// * Each column builds/uses exactly one "vocabulary" (dictionary).
36-
/// * Output columns are KeyType-valued.
37-
/// * The Key value is the one-based index of the item in the dictionary.
38-
/// * Not found is assigned the value zero.
39-
/// </summary>
32+
33+
// TermTransform builds up term vocabularies (dictionaries).
34+
// Notes:
35+
// * Each column builds/uses exactly one "vocabulary" (dictionary).
36+
// * Output columns are KeyType-valued.
37+
// * The Key value is the one-based index of the item in the dictionary.
38+
// * Not found is assigned the value zero.
39+
/// <include file='doc.xml' path='doc/members/member[@name="TextToKey"]/*' />
4040
public sealed partial class TermTransform : OneToOneTransformBase, ITransformTemplate
4141
{
4242
public abstract class ColumnBase : OneToOneColumn

‎src/Microsoft.ML.Data/Transforms/doc.xml

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@@ -0,0 +1,54 @@
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<?xml version="1.0" encoding="utf-8" ?>
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<doc>
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<members>
4+
<member name="NAFilter">
5+
<summary>
6+
Removes missing values from vector type columns.
7+
</summary>
8+
<remarks>
9+
This transform removes the entire row if any of the input columns have a missing value in that row.
10+
This preprocessing is required for many ML algorithms that cannot work with missing values.
11+
Useful if any missing entry invalidates the entire row.
12+
If the <see cref="Microsoft.ML.Runtime.Data.NAFilter.Defaults.Complement"/> is set to true, this transform would do the exact opposite,
13+
it will keep only the rows that have missing values.
14+
</remarks>
15+
<seealso cref="Microsoft.ML.Runtime.Data.MetadataUtils.Kinds.HasMissingValues"></seealso>
16+
</member>
17+
<example name="NAFilter">
18+
<example>
19+
<code language="csharp">
20+
pipeline.Add(new MissingValuesRowDropper(&quot;Column1&quot;));
21+
</code>
22+
</example>
23+
</example>
24+
25+
<member name="TextToKey">
26+
<summary>
27+
Converts input values (words, numbers, etc.) to index in a dictionary.
28+
</summary>
29+
<remarks>
30+
The TextToKeyConverter transform builds up term vocabularies (dictionaries).
31+
The TextToKey Converter and the <see cref="T:Microsoft.ML.Transforms.HashConverter"/> are the two one primary mechanisms by which raw input is transformed into keys.
32+
If multiple columns are used, each column builds/uses exactly one vocabulary.
33+
The output columns are KeyType-valued.
34+
The Key value is the one-based index of the item in the dictionary.
35+
If the key is not found in the dictionary, it is assigned the missing value indicator.
36+
This dictionary mapping values to keys is most commonly learnt from the unique values in input data,
37+
but can be defined through other means: either with the mapping defined directly on the command line, or as loaded from an external file.
38+
</remarks>
39+
<seealso cref="T:Microsoft.ML.Transforms.HashConverter"/>
40+
<seealso cref="T:Microsoft.ML.Transforms.KeyToTextConverter"/>
41+
</member>
42+
<example name="TextToKey">
43+
<example>
44+
<code language="csharp">
45+
pipeline.Add(new TextToKeyConverter((&quot;Column&quot;, &quot;OutColumn&quot;))
46+
{
47+
Sort = TermTransformSortOrder.Occurrence
48+
});
49+
</code>
50+
</example>
51+
</example>
52+
53+
</members>
54+
</doc>

‎src/Microsoft.ML.FastTree/FastTreeArguments.cs

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@@ -20,7 +20,7 @@ public interface IFastTreeTrainerFactory : IComponentFactory<ITrainer>
2020
{
2121
}
2222

23-
/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
23+
/// <include file='doc.xml' path='doc/members/member[@name="FastTree"]/*' />
2424
public sealed partial class FastTreeBinaryClassificationTrainer
2525
{
2626
[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
100100
public override PredictionKind PredictionKind => PredictionKind.BinaryClassification;
101101
}
102102

103-
/// <include file = './doc.xml' path='docs/members/member[@name="FastTree"]/*' />
103+
/// <include file = 'doc.xml' path='doc/members/member[@name="FastTree"]/*' />
104104
public sealed partial class FastTreeBinaryClassificationTrainer :
105105
BoostingFastTreeTrainerBase<FastTreeBinaryClassificationTrainer.Arguments, IPredictorWithFeatureWeights<Float>>
106106
{
@@ -342,7 +342,8 @@ public static partial class FastTree
342342
Desc = FastTreeBinaryClassificationTrainer.Summary,
343343
UserName = FastTreeBinaryClassificationTrainer.UserNameValue,
344344
ShortName = FastTreeBinaryClassificationTrainer.ShortName,
345-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
345+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastTree""]/*' />",
346+
@"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/example[@name=""FastTreeBinaryClassifier""]/*' />" })]
346347
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input)
347348
{
348349
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeRanking.cs

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@@ -38,7 +38,7 @@
3838

3939
namespace Microsoft.ML.Runtime.FastTree
4040
{
41-
/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
41+
/// <include file='doc.xml' path='doc/members/member[@name="FastTree"]/*' />
4242
public sealed partial class FastTreeRankingTrainer : BoostingFastTreeTrainerBase<FastTreeRankingTrainer.Arguments, FastTreeRankingPredictor>,
4343
IHasLabelGains
4444
{
@@ -1096,7 +1096,8 @@ public static partial class FastTree
10961096
Desc = FastTreeRankingTrainer.Summary,
10971097
UserName = FastTreeRankingTrainer.UserNameValue,
10981098
ShortName = FastTreeRankingTrainer.ShortName,
1099-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
1099+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastTree""]/*' />",
1100+
@"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/example[@name=""FastTreeRanker""]/*' />"})]
11001101
public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, FastTreeRankingTrainer.Arguments input)
11011102
{
11021103
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeRegression.cs

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@@ -31,7 +31,7 @@
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3232
namespace Microsoft.ML.Runtime.FastTree
3333
{
34-
/// <include file='./doc.xml' path='docs/members/member[@name="FastTree"]/*' />
34+
/// <include file='doc.xml' path='doc/members/member[@name="FastTree"]/*' />
3535
public sealed partial class FastTreeRegressionTrainer : BoostingFastTreeTrainerBase<FastTreeRegressionTrainer.Arguments, FastTreeRegressionPredictor>
3636
{
3737
public const string LoadNameValue = "FastTreeRegression";
@@ -445,7 +445,8 @@ public static partial class FastTree
445445
Desc = FastTreeRegressionTrainer.Summary,
446446
UserName = FastTreeRegressionTrainer.UserNameValue,
447447
ShortName = FastTreeRegressionTrainer.ShortName,
448-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTree""]/*' />" })]
448+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastTree""]/*' />",
449+
@"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/example[@name=""FastTreeRegressor""]/*' />"})]
449450
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Arguments input)
450451
{
451452
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/FastTreeTweedie.cs

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@@ -30,7 +30,7 @@ namespace Microsoft.ML.Runtime.FastTree
3030
// The Tweedie boosting model follows the mathematics established in:
3131
// Yang, Quan, and Zou. "Insurance Premium Prediction via Gradient Tree-Boosted Tweedie Compound Poisson Models."
3232
// https://arxiv.org/pdf/1508.06378.pdf
33-
/// <include file='./doc.xml' path='docs/members/member[@name="FastTreeTweedieRegression"]/*' />
33+
/// <include file='doc.xml' path='doc/members/member[@name="FastTreeTweedieRegression"]/*' />
3434
public sealed partial class FastTreeTweedieTrainer : BoostingFastTreeTrainerBase<FastTreeTweedieTrainer.Arguments, FastTreeTweediePredictor>
3535
{
3636
public const string LoadNameValue = "FastTreeTweedieRegression";
@@ -454,7 +454,7 @@ public static partial class FastTree
454454
Desc = FastTreeTweedieTrainer.Summary,
455455
UserName = FastTreeTweedieTrainer.UserNameValue,
456456
ShortName = FastTreeTweedieTrainer.ShortName,
457-
XmlInclude = new [] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastTreeTweedieRegression""]/*' />" })]
457+
XmlInclude = new [] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastTreeTweedieRegression""]/*' />" })]
458458
public static CommonOutputs.RegressionOutput TrainTweedieRegression(IHostEnvironment env, FastTreeTweedieTrainer.Arguments input)
459459
{
460460
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/RandomForestClassification.cs

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106106
}
107107
}
108108

109-
/// <include file='./doc.xml' path='docs/members/member[@name="FastForest"]/*' />
109+
/// <include file='doc.xml' path='doc/members/member[@name="FastForest"]/*' />
110110
public sealed partial class FastForestClassification :
111111
RandomForestTrainerBase<FastForestClassification.Arguments, IPredictorWithFeatureWeights<Float>>
112112
{
@@ -206,7 +206,8 @@ public static partial class FastForest
206206
Desc = FastForestClassification.Summary,
207207
UserName = FastForestClassification.UserNameValue,
208208
ShortName = FastForestClassification.ShortName,
209-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
209+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastForest""]/*' />",
210+
@"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/example[@name=""FastForestBinaryClassifier""]/*' />"})]
210211
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestClassification.Arguments input)
211212
{
212213
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/RandomForestRegression.cs

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@@ -137,7 +137,7 @@ public ISchemaBindableMapper CreateMapper(Double[] quantiles)
137137
}
138138
}
139139

140-
/// <include file='./doc.xml' path='docs/members/member[@name="FastForest"]/*' />
140+
/// <include file='doc.xml' path='doc/members/member[@name="FastForest"]/*' />
141141
public sealed partial class FastForestRegression : RandomForestTrainerBase<FastForestRegression.Arguments, FastForestRegressionPredictor>
142142
{
143143
public sealed class Arguments : FastForestArgumentsBase
@@ -277,7 +277,8 @@ public static partial class FastForest
277277
Desc = FastForestRegression.Summary,
278278
UserName = FastForestRegression.LoadNameValue,
279279
ShortName = FastForestRegression.ShortName,
280-
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='docs/members/member[@name=""FastForest""]/*' />" })]
280+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""FastForest""]/*' />",
281+
@"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/example[@name=""FastForestRegressor""]/*' />"})]
281282
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegression.Arguments input)
282283
{
283284
Contracts.CheckValue(env, nameof(env));

‎src/Microsoft.ML.FastTree/Training/Parallel/IParallelTraining.cs

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@@ -33,20 +33,20 @@ public delegate void FindBestThresholdFromRawArrayFun(LeafSplitCandidates leafSp
3333
/// <summary>
3434
/// Interface used for parallel training.
3535
/// Mainly contains three parts:
36-
/// 1. interactive with IO: <see href="GetLocalBinConstructionFeatures" />, <see href="SyncGlobalBoundary" />.
36+
/// 1. interactive with IO: <see cref="GetLocalBinConstructionFeatures" />, <see cref="SyncGlobalBoundary" />.
3737
/// Data will be partitioned by rows in Data parallel and Voting Parallel.
3838
/// To speed up the find bin process, it let different workers to find bins for different features.
3939
/// Then perform global sync up.
4040
/// In Feature parallel, every machines holds all data, so this is unneeded.
41-
/// 2. interactive with TreeLearner: <see href="InitIteration" />, <see href="CacheHistogram" />, <see href="IsNeedFindLocalBestSplit" />,
42-
/// <see href="IsSkipNonSplittableHistogram" />, <see href="FindGlobalBestSplit" />, <see href="GetGlobalDataCountInLeaf" />, <see href="PerformGlobalSplit" />.
41+
/// 2. interactive with TreeLearner: <see cref="InitIteration" />, <see cref="CacheHistogram" />, <see cref="IsNeedFindLocalBestSplit" />,
42+
/// <see cref="IsSkipNonSplittableHistogram" />, <see cref="FindGlobalBestSplit" />, <see cref="GetGlobalDataCountInLeaf" />, <see cref="PerformGlobalSplit" />.
4343
/// A full process is:
44-
/// Use <see href="InitIteration" /> to alter local active features.
45-
/// Use <see href="GetGlobalDataCountInLeaf" /> to check smaller leaf and larger leaf.
46-
/// Use <see href="CacheHistogram" />, <see href="IsNeedFindLocalBestSplit" /> and <see href="IsSkipNonSplittableHistogram" /> to interactive with Feature histograms.
47-
/// Use <see href="FindGlobalBestSplit" /> to sync up global best split
48-
/// Use <see href="PerformGlobalSplit" /> to record global num_data in leaves.
49-
/// 3. interactive with Application : <see href="GlobalMean" />.
44+
/// Use <see cref="InitIteration" /> to alter local active features.
45+
/// Use <see cref="GetGlobalDataCountInLeaf" /> to check smaller leaf and larger leaf.
46+
/// Use <see cref="CacheHistogram" />, <see cref="IsNeedFindLocalBestSplit" /> and <see cref="IsSkipNonSplittableHistogram" /> to interactive with Feature histograms.
47+
/// Use <see cref="FindGlobalBestSplit" /> to sync up global best split
48+
/// Use <see cref="PerformGlobalSplit" /> to record global num_data in leaves.
49+
/// 3. interactive with Application : <see cref="GlobalMean" />.
5050
/// Output of leaves is calculated by newton step ( - sum(first_order_gradients) / sum(second_order_gradients)).
5151
/// If data is partitioned by row, it needs to a sync up for these sum result.
5252
/// So It needs to call this to get the real output of leaves.

‎src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs

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@@ -544,6 +544,7 @@ public ISchemaBoundMapper Bind(IHostEnvironment env, RoleMappedSchema schema)
544544
}
545545
}
546546

547+
/// <include file='doc.xml' path='doc/members/member[@name="TreeEnsembleFeaturizerTransform"]'/>
547548
public static class TreeEnsembleFeaturizerTransform
548549
{
549550
public sealed class Arguments : TrainAndScoreTransform.ArgumentsBase<SignatureTreeEnsembleTrainer>
@@ -802,7 +803,11 @@ private static IDataView AppendLabelTransform(IHostEnvironment env, IChannel ch,
802803

803804
public static partial class TreeFeaturize
804805
{
805-
[TlcModule.EntryPoint(Name = "Transforms.TreeLeafFeaturizer", Desc = TreeEnsembleFeaturizerTransform.TreeEnsembleSummary, UserName = TreeEnsembleFeaturizerTransform.UserName, ShortName = TreeEnsembleFeaturizerBindableMapper.LoadNameShort)]
806+
[TlcModule.EntryPoint(Name = "Transforms.TreeLeafFeaturizer",
807+
Desc = TreeEnsembleFeaturizerTransform.TreeEnsembleSummary,
808+
UserName = TreeEnsembleFeaturizerTransform.UserName,
809+
ShortName = TreeEnsembleFeaturizerBindableMapper.LoadNameShort,
810+
XmlInclude = new[] { @"<include file='../Microsoft.ML.FastTree/doc.xml' path='doc/members/member[@name=""TreeEnsembleFeaturizerTransform""]'/>" })]
806811
public static CommonOutputs.TransformOutput Featurizer(IHostEnvironment env, TreeEnsembleFeaturizerTransform.ArgumentsForEntryPoint input)
807812
{
808813
Contracts.CheckValue(env, nameof(env));

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