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Created samples for StochasticGradientDescentNonCalibrated learner. #2770
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Codecov Report
@@ Coverage Diff @@
## master #2770 +/- ##
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Coverage ? 71.65%
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Files ? 807
Lines ? 142374
Branches ? 16120
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Hits ? 102025
Misses ? 35915
Partials ? 4434
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Codecov Report
@@ Coverage Diff @@
## master #2770 +/- ##
=========================================
Coverage ? 71.68%
=========================================
Files ? 808
Lines ? 142392
Branches ? 16112
=========================================
Hits ? 102073
Misses ? 35888
Partials ? 4431
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var mlContext = new MLContext(seed: 0); | ||
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// Download and featurize the dataset. | ||
var data = SamplesUtils.DatasetUtils.LoadFeaturizedAdultDataset(mlContext); |
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It'd nice if you can use in-memory data for trainers. Such a way has some benefits as discussed in #2726. #WontFix
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Lets do these things once we have decision.
In reply to: 261770052 [](ancestors = 261770052,261020122)
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// Evaluate how the model is doing on the test data. | ||
var dataWithPredictions = model.Transform(trainTestData.TestSet); | ||
var metrics = mlContext.BinaryClassification.EvaluateNonCalibrated(dataWithPredictions); |
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Need to show how user can inspect the prediction example-by-example. Evaluation is not the major part in products. #WontFix
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/// <example> | ||
/// <format type="text/markdown"> | ||
/// <] |
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StochasticGradientDescentWithOptions [](start = 26, length = 36)
please fix this copy-paste error. #Resolved
/// /// <example> | ||
/// <format type="text/markdown"> | ||
/// <] |
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StochasticGradientDescentWithOptions [](start = 26, length = 36)
same here #Resolved
Created samples for StochasticGradientDescentNonCalibrated learner exposed via following methods.
machinelearning/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs
Line 82 in a0edc5c
machinelearning/src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs
Line 102 in a0edc5c