Defaults for ImageClassification API #4415
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eerhardt
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Oct 31, 2019
eerhardt
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Nov 1, 2019
added 3 commits
November 1, 2019 12:04
…s been update to show how to get the output to console from the log.
harshithapv
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codemzs
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Nov 1, 2019
| //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
codemzs
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Nov 1, 2019
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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
codemzs
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Nov 1, 2019
| options.ValidationSetBottleneckCachedValuesFileName = _options.ValidationSetBottleneckCachedValuesFileName; | ||
| } | ||
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| if ( options.MetricsCallback == null ) |
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[](start = 16, length = 1)
space #Closed
codemzs
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Nov 1, 2019
| options.ValidationSetBottleneckCachedValuesFileName = _options.ValidationSetBottleneckCachedValuesFileName; | ||
| } | ||
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| if ( options.MetricsCallback == null ) |
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[](start = 48, length = 1)
space #Closed
frank-dong-ms-zz
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Nov 4, 2019
* 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.
frank-dong-ms-zz
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Nov 4, 2019
* 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.
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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.