Microsoft.ML.Transforms.TimeSeries Namespace
Important
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Namespace containing time-series data transformation components.
Classes
| IidAnomalyDetectionBaseWrapper |
The is the wrapper to Microsoft.ML.Transforms.TimeSeries.IidAnomalyDetectionBaseWrapper.IidAnomalyDetectionBase that computes the p-values and martingale scores for a supposedly i.i.d input sequence of floats. In other words, it assumes the input sequence represents the raw anomaly score which might have been computed via another process. |
| IidChangePointDetector |
ITransformer resulting from fitting a IidChangePointEstimator. |
| IidChangePointEstimator |
Detect a signal change on an independent identically distributed (i.i.d.) time series based on adaptive kernel density estimation and martingales. |
| IidSpikeDetector |
ITransformer resulting from fitting a IidSpikeEstimator. |
| IidSpikeEstimator |
Detect a signal spike on an independent identically distributed (i.i.d.) time series based on adaptive kernel density estimation. |
| PredictionFunctionExtensions | |
| SrCnnAnomalyDetectionBase | |
| SrCnnAnomalyDetector |
ITransformer resulting from fitting a SrCnnAnomalyEstimator. |
| SrCnnAnomalyEstimator |
Detect anomalies in time series using Spectral Residual(SR) algorithm |
| SsaAnomalyDetectionBaseWrapper |
The wrapper to Microsoft.ML.Transforms.TimeSeries.SsaAnomalyDetectionBaseWrapper.SsaAnomalyDetectionBase that implements the general anomaly detection transform based on Singular Spectrum modeling of the time-series. For the details of the Singular Spectrum Analysis (SSA), refer to http://arxiv.org/pdf/1206.6910.pdf. |
| SsaChangePointDetector |
ITransformer resulting from fitting a SsaChangePointEstimator. |
| SsaChangePointEstimator |
Detect change points in time series using Singular Spectrum Analysis. |
| SsaForecastingBaseWrapper |
The wrapper to Microsoft.ML.Transforms.TimeSeries.SsaForecastingBaseWrapper.SsaForecastingBase that implements the general anomaly detection transform based on Singular Spectrum modeling of the time-series. For the details of the Singular Spectrum Analysis (SSA), refer to http://arxiv.org/pdf/1206.6910.pdf. |
| SsaForecastingEstimator |
Forecasts using Singular Spectrum Analysis. |
| SsaForecastingTransformer |
ITransformer resulting from fitting a SsaForecastingEstimator. |
| SsaSpikeDetector |
ITransformer resulting from fitting a SsaSpikeEstimator. |
| SsaSpikeEstimator |
Detect spikes in time series using Singular Spectrum Analysis. |
| TimeSeriesPredictionEngine<TSrc,TDst> |
A class that runs the previously trained model (and the preceding transform pipeline) on the in-memory data, one example at a time. This can also be used with trained pipelines that do not end with a predictor: in this case, the 'prediction' will be just the outcome of all the transformations. |
Structs
| GrowthRatio |
Growth ratio. Defined as Growth^(1/TimeSpan). |
Enums
| AnomalySide |
The side of anomaly detection. |
| ErrorFunction | |
| MartingaleType |
The type of the martingale. |
| RankSelectionMethod |
Ranking selection method for the signal. |