Add LR XML doc #3385

wschin · 2019-04-17T21:09:20Z

Toward #2522 following #3218.

shmoradims · 2019-04-17T23:16:14Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

@@ -27,8 +27,55 @@
 namespace Microsoft.ML.Trainers
 {

-    /// <include file='doc.xml' path='doc/members/member[@name="LBFGS"]/*' />


file='doc.xml' path='doc/members/member[@name="LBFGS"]/* [](start = 17, length = 56)

please delete these sections that you moved here from doc.xml #Resolved

singlis · 2019-04-17T23:17:11Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

+    ///
+    /// [!include[io](~/../docs/samples/docs/api-reference/io-columns-binary-classification.md)]
+    ///
+    /// ### Trainer Characteristics


Should this be Estimator Characteristics? #Resolved

No. I don't see others are doing Estimator.

In reply to: 276468119 [](ancestors = 276468119)

shmoradims · 2019-04-17T23:20:06Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

+    /// </summary>
+    /// <remarks>
+    /// <format type="text/markdown"><![CDATA[
+    /// To create this trainer, use [LbfgsLogisticRegression](xref:Microsoft.ML.StandardTrainersCatalog.LbfgsLogisticRegression(BinaryClassificationCatalog.BinaryClassificationTrainers, string, string, string, float, float, float, int, bool))


LbfgsLogisticRegression(BinaryClassificationCatalog.BinaryClassificationTrainers, string, string, string, float, float, float, int, bool)) [](start = 104, length = 138)

this UID won't work, you need fully qualified names. please use https://xref.docs.microsoft.com/autocomplete?text=LbfgsLogisticRegression to get the UID. It's this one:

Microsoft.ML.StandardTrainersCatalog.LbfgsLogisticRegression(Microsoft.ML.BinaryClassificationCatalog.BinaryClassificationTrainers,System.String,System.String,System.String,System.Single,System.Single,System.Single,System.Int32,System.Boolean)

please also fix for the other one.
#Resolved

Thanks. Sure.

In reply to: 276468758 [](ancestors = 276468758)

shmoradims · 2019-04-17T23:21:24Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

@@ -39,6 +86,10 @@ public sealed partial class LbfgsLogisticRegressionBinaryTrainer : LbfgsTrainerB
        internal const string Summary = "Logistic Regression is a method in statistics used to predict the probability of occurrence of an event and can "
            + "be used as a classification algorithm. The algorithm predicts the probability of occurrence of an event by fitting data to a logistical function.";

+        /// <summary>
+        /// Options for the <see cref="LbfgsLogisticRegressionBinaryTrainer"/> as used in
+        /// [LbfgsLogisticRegression(Options)](xref:Microsoft.ML.StandardTrainersCatalog.LbfgsLogisticRegression(BinaryClassificationCatalog.BinaryClassificationTrainers, LbfgsLogisticRegressionBinaryTrainer.Options)).


(xref:Microsoft.ML.StandardTrainersCat [](start = 46, length = 38)

ditto: fix uid

more info: https://microsoft.sharepoint.com/teams/ML.NET/_layouts/OneNote.aspx?id=%2Fteams%2FML.NET%2FSiteAssets%2FML.NET%20Notebook&wd=target%28Specs.one%7C19A109F5-7BDE-4447-B63E-3934EAD9615D%2FML.Net%20API%20documentation%20fit%20and%20finish%7CC15DB5A6-712C-469F-BDED-5B02554A1238%2F%29
onenote:https://microsoft.sharepoint.com/teams/ML.NET/SiteAssets/ML.NET%20Notebook/Specs.one#ML.Net%20API%20documentation%20fit%20and%20finish&section-id={19A109F5-7BDE-4447-B63E-3934EAD9615D}&page-id={C15DB5A6-712C-469F-BDED-5B02554A1238}&object-id={22B72EA3-D558-0174-3C77-B4F095C6FB0D}&B #Resolved

codecov · 2019-04-18T22:05:46Z

Codecov Report

Merging #3385 into master will increase coverage by 0.06%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #3385      +/-   ##
==========================================
+ Coverage   72.69%   72.76%   +0.06%     
==========================================
  Files         807      808       +1     
  Lines      145172   145452     +280     
  Branches    16225    16244      +19     
==========================================
+ Hits       105538   105838     +300     
+ Misses      35220    35192      -28     
- Partials     4414     4422       +8

Flag	Coverage Δ
#Debug	`72.76% <ø> (+0.06%)`	⬆️
#production	`68.27% <ø> (+0.04%)`	⬆️
#test	`89.04% <ø> (+0.06%)`	⬆️

Impacted Files	Coverage Δ
.../Standard/LogisticRegression/LogisticRegression.cs	`94.95% <ø> (ø)`	⬆️
...oft.ML.StandardTrainers/StandardTrainersCatalog.cs	`92.34% <ø> (ø)`	⬆️
src/Microsoft.ML.Data/Transforms/KeyToValue.cs	`79.16% <0%> (-0.65%)`	⬇️
src/Microsoft.ML.Transforms/Text/LdaTransform.cs	`89.26% <0%> (-0.63%)`	⬇️
...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)`	⬆️
... and 57 more

codemzs · 2019-04-19T22:35:51Z

src/Microsoft.ML.StandardTrainers/StandardTrainersCatalog.cs

@@ -518,11 +518,11 @@ public IClassificationLoss CreateComponent(IHostEnvironment env)
        }

        /// <summary>
-        ///  Predict a target using a linear binary classification model trained with the <see cref="Trainers.LbfgsLogisticRegressionBinaryTrainer"/> trainer.
+        ///  Create an <see cref="Trainers.LbfgsLogisticRegressionBinaryTrainer"/>, which predicts a target using a linear binary classification model trained over boolean label data.


an [](start = 20, length = 2)

Can you please check with Shahab/@natke if we need "an"? In my PRs it was just Create
#Resolved

"Create a" or just "Create" #Resolved

codemzs

singlis · 2019-04-20T00:41:28Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

+    /// An accurate model with extreme coefficient values would be penalized more, but a less accurate model with more conservative values would be penalized less.
+    ///
+    /// This learner supports [elastic net regularization](https://en.wikipedia.org/wiki/Elastic_net_regularization): a linear combination of L1-norm (LASSO), $|| \boldsymbol{w} ||_1$, and L2-norm (ridge), $|| \boldsymbol{w} ||_2^2$ regularizations.
+    /// L1-nrom and L2-norm regularizations have different effects and uses that are complementary in certain respects.


r [](start = 12, length = 1)

L1-norm #Resolved

singlis · 2019-04-20T00:42:19Z

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LogisticRegression.cs

+    /// This learner supports [elastic net regularization](https://en.wikipedia.org/wiki/Elastic_net_regularization): a linear combination of L1-norm (LASSO), $|| \boldsymbol{w} ||_1$, and L2-norm (ridge), $|| \boldsymbol{w} ||_2^2$ regularizations.
+    /// L1-nrom and L2-norm regularizations have different effects and uses that are complementary in certain respects.
+    /// Using L1-norm can increase sparsity of the trained $\boldsymbol{w}$.
+    /// When working with high-dimensional data, it shrinks small weights of irrevalent features to 0 and therefore no reource will be spent on those bad features when making prediction.


irrevalent [](start = 77, length = 10)

irrelavent #Resolved

singlis

Add LR XML doc

9e4b1f8

wschin added the documentation Related to documentation of ML.NET label Apr 17, 2019

wschin requested review from codemzs, yaeldekel, shmoradims and sfilipi April 17, 2019 21:09

wschin self-assigned this Apr 17, 2019

shmoradims mentioned this pull request Apr 17, 2019

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

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singlis reviewed Apr 17, 2019

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wschin added 2 commits April 18, 2019 09:40

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Fix UID

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wschin requested review from shmoradims, codemzs and singlis April 19, 2019 23:25

Fix cref

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singlis reviewed Apr 20, 2019

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wschin added 3 commits April 19, 2019 22:37

Fix ref

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Typos

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Fix typos

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wschin merged commit 6cb5a37 into dotnet:master Apr 20, 2019

wschin deleted the lr-doc branch April 20, 2019 07:22

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Add LR XML doc #3385

Add LR XML doc #3385

wschin commented Apr 17, 2019

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Add LR XML doc #3385

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