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Defaults for ImageClassification API #4415
Defaults for ImageClassification API #4415
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…s been update to show how to get the output to console from the log.
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@@ -29,13 +29,15 @@ public static void Example() | |||
//Download the image set and unzip | |||
string finalImagesFolderName = DownloadImageSet( | |||
imagesDownloadFolderPath); | |||
//string finalImagesFolderName = "flower_photos"; |
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//string finalImagesFolderName = "flower_photos"; [](start = 12, length = 49)
remove #Closed
@@ -60,7 +62,7 @@ public static void Example() | |||
IDataView testDataset = trainTestData.TestSet; | |||
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var pipeline = mlContext.MulticlassClassification.Trainers | |||
.ImageClassification(featureColumnName:"Image", validationSet:testDataset) | |||
.ImageClassification(featureColumnName:"Image", validationSet:null) |
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, validationSet:null [](start = 70, length = 20)
no need, default is null. #Resolved
@@ -532,6 +532,12 @@ internal ImageClassificationTrainer(IHostEnvironment env, Options options) | |||
options.ValidationSetBottleneckCachedValuesFileName = _options.ValidationSetBottleneckCachedValuesFileName; | |||
} | |||
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if ( options.MetricsCallback == null ) |
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[](start = 16, length = 1)
space #Closed
@@ -532,6 +532,12 @@ internal ImageClassificationTrainer(IHostEnvironment env, Options options) | |||
options.ValidationSetBottleneckCachedValuesFileName = _options.ValidationSetBottleneckCachedValuesFileName; | |||
} | |||
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if ( options.MetricsCallback == null ) |
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[](start = 48, length = 1)
space #Closed
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* Changed some defaults * Changed metrics callback default * metricsCallback will write to mlcontext log by default. The sample has been update to show how to get the output to console from the log. * deleted unnecessary comments * Addressed comments * Minor clean up. * Disable unstable test.
* Changed some defaults * Changed metrics callback default * metricsCallback will write to mlcontext log by default. The sample has been update to show how to get the output to console from the log. * deleted unnecessary comments * Addressed comments * Minor clean up. * Disable unstable test.
Changed EarlyStopping to run by default with ExponentialLR Decay for learning rate scheduling.
This combination seems to give most optimal results with a trade-off balance between the accuracy and training time.