FFM XML Doc And Add One Missing Sample File #3374

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wschin merged 9 commits into dotnet:master from wschin:ffm-doc

Apr 20, 2019

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wschin commented Apr 17, 2019

Toward #2522 following #3218.

wschin added 2 commits

April 17, 2019 09:20


          Update major FFM doc

b500dc6


          Add missing sample file

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wschin requested review from codemzs, Ivanidzo4ka, shmoradims and rogancarr

April 17, 2019 17:19

wschin self-assigned this

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Docs and samples for the API reference site (P0 & P1 Trainers) #2522

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codecov bot commented Apr 17, 2019 •

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Codecov Report

Merging #3374 into master will increase coverage by 0.07%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #3374      +/-   ##
==========================================
+ Coverage    72.7%   72.77%   +0.07%     
==========================================
  Files         807      808       +1     
  Lines      145172   145452     +280     
  Branches    16225    16244      +19     
==========================================
+ Hits       105541   105849     +308     
+ Misses      35217    35183      -34     
- Partials     4414     4420       +6

Flag	Coverage Δ
#Debug	`72.77% <ø> (+0.07%)`	⬆️
#production	`68.28% <ø> (+0.04%)`	⬆️
#test	`89.05% <ø> (+0.06%)`	⬆️

Impacted Files	Coverage Δ
...actorizationMachine/FactorizationMachineTrainer.cs	`88.47% <ø> (ø)`	⬆️
...actorizationMachine/FactorizationMachineCatalog.cs	`66.66% <ø> (ø)`	⬆️
src/Microsoft.ML.Data/Transforms/KeyToValue.cs	`79.16% <0%> (-0.65%)`	⬇️
...ML.Transforms/MutualInformationFeatureSelection.cs	`78.58% <0%> (-0.33%)`	⬇️
...ML.Transforms/Text/StopWordsRemovingTransformer.cs	`86.1% <0%> (-0.16%)`	⬇️
...ft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs	`77.18% <0%> (-0.01%)`	⬇️
...ML.Data/Transforms/ColumnConcatenatingEstimator.cs	`80.3% <0%> (ø)`	⬆️
...soft.ML.Transforms/Text/WordEmbeddingsExtractor.cs	`87.52% <0%> (ø)`	⬆️
...luators/Metrics/MulticlassClassificationMetrics.cs	`100% <0%> (ø)`	⬆️
src/Microsoft.ML.Recommender/RecommenderCatalog.cs	`70.83% <0%> (ø)`	⬆️
... and 57 more


          Fix UIDs

b28f583

wschin changed the title ~~FFM XML Doc~~ FFM XML Doc And Add One Missing Sample File

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docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/BinaryClassification/FactorizationMachine.cs Show resolved Hide resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Show resolved Hide resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  /// or [FieldAwareFactorizationMachine(Options)](xref:Microsoft.ML.FactorizationMachineExtensions.FieldAwareFactorizationMachine(Microsoft.ML.BinaryClassificationCatalog.BinaryClassificationTrainers,Microsoft.ML.Trainers.FieldAwareFactorizationMachineTrainer.Options)).
+                  ///
+                  /// In contrast to other binary classifiers which can only support one feature column, field-aware factorization machine can consume multiple feature columns.
+                  /// Each column is viewed a container of some fatures and such a container is called a field.

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shauheen Apr 18, 2019 •

edited by wschin

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a container [](start = 29, length = 12)

as #Resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  /// or [FieldAwareFactorizationMachine(Options)](xref:Microsoft.ML.FactorizationMachineExtensions.FieldAwareFactorizationMachine(Microsoft.ML.BinaryClassificationCatalog.BinaryClassificationTrainers,Microsoft.ML.Trainers.FieldAwareFactorizationMachineTrainer.Options)).
+                  ///
+                  /// In contrast to other binary classifiers which can only support one feature column, field-aware factorization machine can consume multiple feature columns.
+                  /// Each column is viewed a container of some fatures and such a container is called a field.

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shauheen Apr 18, 2019 •

edited by wschin

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fatures [](start = 50, length = 7)

features #Resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  ///
+                  /// In contrast to other binary classifiers which can only support one feature column, field-aware factorization machine can consume multiple feature columns.
+                  /// Each column is viewed a container of some fatures and such a container is called a field.
+                  /// The motivation of splitting features into different fields is to model features from different distributions in a different way.

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shauheen Apr 18, 2019 •

edited by wschin

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in a different way [](start = 117, length = 18)

independently #Resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  /// ### Background
+                  /// Factorization machine family is a powerful model group for supervised learning problems.
+                  /// It was first introduced in Steffen Rendle's [Factorization Machines](http://ieeexplore.ieee.org/document/5694074/?reload=true) paper in 2010.
+                  /// Later, one of its generalized version, field-aware factorization machine, became an important predictive module in recent recommender systems and click-through rate prediction contests.

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shauheen Apr 18, 2019 •

edited by wschin

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version [](start = 38, length = 7)

versions #Resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  /// Factorization machine family is a powerful model group for supervised learning problems.
+                  /// It was first introduced in Steffen Rendle's [Factorization Machines](http://ieeexplore.ieee.org/document/5694074/?reload=true) paper in 2010.
+                  /// Later, one of its generalized version, field-aware factorization machine, became an important predictive module in recent recommender systems and click-through rate prediction contests.
+                  /// For examples, see winning solutions in Steffen Rendle's KDD-Cup 2012 ([Track 1](http://www.kdd.org/kdd-cup/view/kdd-cup-2012-track-1) and[Track 2](http://www.kdd.org/kdd-cup/view/kdd-cup-2012-track-2)),

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shauheen Apr 18, 2019 •

edited by wschin

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nd[T [](start = 143, length = 4)

space #Resolved

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineTrainer.cs Outdated

+                  /// The corresponding score is $\hat{y}\left(\boldsymbol{x}\right) = \left\langle \boldsymbol{w}, \boldsymbol{x} \right\rangle + \sum_{j = 1}^n \sum_{j' = j + 1}^n \left\langle \boldsymbol{v}_{j, {\mathcal F}(j')} , \boldsymbol{v}_{j', {\mathcal F}(j)} \right\rangle x_j x_{j'}$,
+                  /// where $\left\langle \cdot, \cdot \right\rangle$ is the inner product operator, $\boldsymbol{w}\in{\mathbb R}^n$ stores the linear coefficients, and $\boldsymbol{v}_{j, f}\in {\mathbb R}^k$ is the $j$-th feature's representation in the $f$-th field's latent space.
+                  /// Note that $k$ is the latent dimension specified by the user.
+                  /// The predicted label is the sign of $\hat{y}$. If $\hat{y} > 0$, this model predicts true and false otherwise.

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shauheen Apr 18, 2019 •

edited by wschin

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nd false otherwise [](start = 98, length = 18)

otherwise it predicts false. #Resolved

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wschin added 2 commits

April 18, 2019 13:58


          Address comments

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          Address a comment

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineCatalog.cs Outdated

    
            @@ -14,19 +14,19 @@ namespace Microsoft.ML
          
                  public static class FactorizationMachineExtensions

                  {

                      /// <summary>

                      /// Predict a target using a field-aware factorization machine algorithm.

                      /// Create an <see cref="FieldAwareFactorizationMachineTrainer"/>, which predicts a target using a field-aware factorization machine trained over boolean label data.

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codemzs Apr 19, 2019 •

edited by wschin

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an [](start = 19, length = 2)

Check with @natke if we need "an" for my PRs there was no "an" or "a" #Resolved

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wschin Apr 19, 2019

Let me just follow you.

In reply to: 277106453 [](ancestors = 277106453)

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src/Microsoft.ML.StandardTrainers/FactorizationMachine/FactorizationMachineCatalog.cs Outdated

    
            @@ -63,10 +64,10 @@ public static class FactorizationMachineExtensions
          
                      }

                      /// <summary>

                      /// Predict a target using a field-aware factorization machine algorithm.

                      /// Create an <see cref="FieldAwareFactorizationMachineTrainer"/>, which predicts a target using a field-aware factorization machine trained over boolean label data.

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codemzs Apr 19, 2019 •

edited by wschin

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Create an [](start = 11, length = 62)

Create using advanced options, ... #Resolved

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wschin and others added 3 commits

April 19, 2019 16:02


          Address comments

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          Fix cref

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          Fix ref

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          Update src/Microsoft.ML.StandardTrainers/FactorizationMachine/Factori…

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…zationMachineCatalog.cs

wschin merged commit 5241462 into dotnet:master

wschin deleted the ffm-doc branch

April 20, 2019 07:20

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codemzs codemzs approved these changes

shauheen shauheen approved these changes

Ivanidzo4ka Awaiting requested review from Ivanidzo4ka

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