SSA time series samples #1788
SSA time series samples #1788
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| // 4 0 2.16 0.00 0.24 | ||
| // 100 0 86.23 0.00 2076098.24 | ||
| // 200 0 171.38 0.00 809668524.21 | ||
| // 300 1 256.83 0.01 22130423541.93 <-- alert is on, note that delay is expected |
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93 <-- alert is on, note that delay is expected [](start = 59, length = 50)
Can you please add the indicator when the mode was saved/loaded? Same for other test. #Resolved
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| // Setup SsaChangePointDetector arguments | ||
| string outputColumnName = "Prediction"; | ||
| string inputColumnName = "Value"; |
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"Value"; [](start = 37, length = 8)
nameof(SsaChangePointData.Value) and same for Prediction as well for both the files. #Resolved
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| var data = new List<SsaSpikeData>(); | ||
| for (int i = 0; i < TrainingSeasons; i++) | ||
| for (int j = 0; j < SeasonalitySize; j++) | ||
| data.Add(new SsaSpikeData(j)); |
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Data generation used accross samples consider moving them in the Microsoft.ML.SamplesUtils.DatasetUtils.
| // 100 1 98.21 0.00 <-- alert is on, predicted spike | ||
| // 0 0 - 13.83 0.29 | ||
| // 1 0 - 1.74 0.44 | ||
| // 2 0 - 0.47 0.46 |
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doe it make sense to limit the preview/data to something smaller,maybe like 7 rows ?
| foreach (var prediction in predictionColumn) | ||
| Console.WriteLine("{0}\t{1:0.00}\t{2:0.00}", prediction.Prediction[0], prediction.Prediction[1], prediction.Prediction[2]); | ||
| Console.WriteLine("{0}\t{1}\t{2:0.00}\t{3:0.00}", data[k++].Value, prediction.Prediction[0], prediction.Prediction[1], prediction.Prediction[2]); | ||
| Console.WriteLine(""); |
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Console.WriteLine(""); [](start = 11, length = 23)
remove, and include the newline in the above.
| foreach (var prediction in predictionColumn) | ||
| Console.WriteLine("{0}\t{1:0.00}\t{2:0.00}", prediction.Prediction[0], prediction.Prediction[1], prediction.Prediction[2]); | ||
| Console.WriteLine("{0}\t{1}\t{2:0.00}\t{3:0.00}", data[k++].Value, prediction.Prediction[0], prediction.Prediction[1], prediction.Prediction[2]); |
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"{0}\t{1}\t{2:0.00}\t{3:0.00}" [](start = 34, length = 30)
think we prefer interpolation.
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| // This example shows spike detection as above, but demonstrates how to train a model | ||
| // that can run predictions on streaming data, and how to persist the trained model and then re-load it. | ||
| public static void SsaSpikeDetectorPrediction() |
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same comment as in the other PR; maybe the end-to-end should go on tutorials. The API call usage should go here.
ghost
locked as resolved and limited conversation to collaborators
Samples for SsaChangePointDetectorPrediction and SsaSpikeDetectorPrediction.