Interface ITimeSeriesRegressionPredictor

    • Method Detail

      • score

        List<TimeSeriesScore<Double>> score​(ArrayList<Map<String,​?>> rows)
        Calculates score for the Time-Series rows. NOTE: rows will be sorted lexicographical order by series_id then by date so adds linear overhead if all data is already sorted and historic data is extracted from the rows to predict by the setted/unsetted to not NaN target values.
        Parameters:
        rows - time-series that contains both historic data and points to predict.
        Returns:
        collection of scores only for the rows to predict.
      • score

        List<TimeSeriesScore<Double>> score​(ArrayList<Map<String,​?>> rows,
                                            String forecastPoint)
        Calculates score for the Time-Series rows. NOTE: rows will be sorted lexicographical order by series_id then by date so adds linear overhead if all data is already sorted. Historic data is extracted from the rows to predict by the forecastPoint.
        Parameters:
        rows - time-series that contains both historic data and points to predict.
        forecastPoint - date from which to start predictions.
        Returns:
        collection of scores only for the rows to predict.
      • score

        List<TimeSeriesScore<Double>> score​(ArrayList<Map<String,​?>> rows,
                                            String startDate,
                                            String endDate)
        Calculates historical scores for the Time-Series rows. NOTE: rows is expected to be sorted by the date, and contains only historic data.
        Parameters:
        rows - history time-series.
        startDate - start date for historical predictions.
        endDate - end date for historical predictions.
        Returns:
        collection of scores only for the rows between startDate and endDate.
      • score

        List<TimeSeriesScore<Double>> score​(ArrayList<Map<String,​?>> rows,
                                            TimeSeriesOptions options)
        Generalized method for calculating predictons could be used for any type of predictions.
        Parameters:
        rows - - time series to use for calculate predictions.
        options - - ts scoring options
        Returns:
        predictions according to the options provided.