Checkpointing time series using Singular Spectrum Analysis (SSA) model

This code is using the CheckPoint method of the TimeSeriesPredictionEngine class in ML.NET. This method saves the state of the time series model to a file, so that it can be loaded and used for predictions later. For example, if you have a time series model that detects change points in data, you can use the CheckPoint method to save the model after training and then load it in another application to make predictions on new data.

SsaForecastingTransformer forecaster = forecastingPipeline.Fit(trainingData);

var forecastEngine = forecaster.CreateTimeSeriesEngine<ModelInput, ModelOutput>(mlContext);

// save model zip file
forecastEngine.CheckPoint(mlContext, ModelPath);