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Update cookbook #2494

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merged 4 commits into from Feb 11, 2019
Merged

Update cookbook #2494

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d56d14b
Switch OneHotEncoding parameters
jwood803 Feb 11, 2019
fbb5cc9
Merge branch 'master' into update-cookbook
jwood803 Feb 11, 2019
760e9a3
Fix table of contents
jwood803 Feb 11, 2019
faa39fd
Update for spacing
jwood803 Feb 11, 2019
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6 changes: 3 additions & 3 deletions docs/code/MlNetCookBook.md
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Expand Up @@ -688,11 +688,11 @@ var catColumns = data.GetColumn<string[]>(mlContext, "CategoricalFeatures").Take
// Build several alternative featurization pipelines.
var pipeline =
// Convert each categorical feature into one-hot encoding independently.
mlContext.Transforms.Categorical.OneHotEncoding("CategoricalFeatures", "CategoricalOneHot")
mlContext.Transforms.Categorical.OneHotEncoding("CategoricalOneHot", "CategoricalFeatures")
// Convert all categorical features into indices, and build a 'word bag' of these.
.Append(mlContext.Transforms.Categorical.OneHotEncoding("CategoricalFeatures", "CategoricalBag", CategoricalTransform.OutputKind.Bag))
.Append(mlContext.Transforms.Categorical.OneHotEncoding("CategoricalBag", "CategoricalFeatures", CategoricalTransform.OutputKind.Bag))
// One-hot encode the workclass column, then drop all the categories that have fewer than 10 instances in the train set.
.Append(mlContext.Transforms.Categorical.OneHotEncoding("Workclass", "WorkclassOneHot"))
.Append(mlContext.Transforms.Categorical.OneHotEncoding("WorkclassOneHot", "Workclass"))
.Append(mlContext.Transforms.FeatureSelection.CountFeatureSelectingEstimator("WorkclassOneHot", "WorkclassOneHotTrimmed", count: 10));

// Let's train our pipeline, and then apply it to the same data.
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