Datetime Trend Plots

class datarobot.models.datetime_trend_plots.AccuracyOverTimePlotsMetadata(project_id, model_id, forecast_distance, resolutions, backtest_metadata, holdout_metadata, backtest_statuses, holdout_statuses)

Accuracy over Time metadata for datetime model.

Added in version v2.25.

Notes

Backtest/holdout status is a dict containing the following:

• training: string

  Status backtest/holdout training. One of datarobot.enums.DATETIME_TREND_PLOTS_STATUS

• validation: string

  Status backtest/holdout validation. One of datarobot.enums.DATETIME_TREND_PLOTS_STATUS

Backtest/holdout metadata is a dict containing the following:

• training: dict

  Start and end dates for the backtest/holdout training.

• validation: dict

  Start and end dates for the backtest/holdout validation.

Each dict in the training and validation in backtest/holdout metadata is structured like:

• start_date: datetime.datetime or None

  The datetime of the start of the chart data (inclusive). None if chart data is not computed.

• end_date: datetime.datetime or None

  The datetime of the end of the chart data (exclusive). None if chart data is not computed.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

forecast_distance: int or None

The forecast distance for which the metadata was retrieved. None for OTV projects.

resolutions: list of string

A list of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION, which represents available time resolutions for which plots can be retrieved.

backtest_metadata: list of dict

List of backtest metadata dicts. The list index of metadata dict is the backtest index. See backtest/holdout metadata info in Notes for more details.

holdout_metadata: dict

Holdout metadata dict. See backtest/holdout metadata info in Notes for more details.

backtest_statuses: list of dict

List of backtest statuses dict. The list index of status dict is the backtest index. See backtest/holdout status info in Notes for more details.

holdout_statuses: dict

Holdout status dict. See backtest/holdout status info in Notes for more details.

class datarobot.models.datetime_trend_plots.AccuracyOverTimePlot(project_id, model_id, start_date, end_date, resolution, bins, statistics, calendar_events)

Accuracy over Time plot for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

• actual: float or None

  Average actual value of the target in the bin. None if there are no entries in the bin.

• predicted: float or None

  Average prediction of the model in the bin. None if there are no entries in the bin.

• frequency: int or None

  Indicates number of values averaged in bin.

Statistics is a dict containing the following:

• durbin_watson: float or None

  The Durbin-Watson statistic for the chart data. Value is between 0 and 4. Durbin-Watson statistic is a test statistic used to detect the presence of autocorrelation at lag 1 in the residuals (prediction errors) from a regression analysis. More info https://wikipedia.org/wiki/Durbin%E2%80%93Watson_statistic

Calendar event is a dict containing the following:

• name: string

  Name of the calendar event.

• date: datetime

  Date of the calendar event.

• series_id: string or None

  The series ID for the event. If this event does not specify a series ID, then this will be None, indicating that the event applies to all series.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

resolution: string

The resolution that is used for binning. One of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.

statistics: dict

Statistics for plot. See statistics info in Notes for more details.

calendar_events: list of dict

List of calendar events for the plot. See calendar events info in Notes for more details.

class datarobot.models.datetime_trend_plots.AccuracyOverTimePlotPreview(project_id, model_id, start_date, end_date, bins)

Accuracy over Time plot preview for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

• actual: float or None

  Average actual value of the target in the bin. None if there are no entries in the bin.

• predicted: float or None

  Average prediction of the model in the bin. None if there are no entries in the bin.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.

class datarobot.models.datetime_trend_plots.ForecastVsActualPlotsMetadata(project_id, model_id, resolutions, backtest_metadata, holdout_metadata, backtest_statuses, holdout_statuses)

Forecast vs Actual plots metadata for datetime model.

Added in version v2.25.

Notes

Backtest/holdout status is a dict containing the following:

• training: dict

  Dict containing each of datarobot.enums.DATETIME_TREND_PLOTS_STATUS as dict key, and list of forecast distances for particular status as dict value.

• validation: dict

  Dict containing each of datarobot.enums.DATETIME_TREND_PLOTS_STATUS as dict key, and list of forecast distances for particular status as dict value.

Backtest/holdout metadata is a dict containing the following:

• training: dict

  Start and end dates for the backtest/holdout training.

• validation: dict

  Start and end dates for the backtest/holdout validation.

Each dict in the training and validation in backtest/holdout metadata is structured like:

• start_date: datetime.datetime or None

  The datetime of the start of the chart data (inclusive). None if chart data is not computed.

• end_date: datetime.datetime or None

  The datetime of the end of the chart data (exclusive). None if chart data is not computed.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

resolutions: list of string

A list of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION, which represents available time resolutions for which plots can be retrieved.

backtest_metadata: list of dict

List of backtest metadata dicts. The list index of metadata dict is the backtest index. See backtest/holdout metadata info in Notes for more details.

holdout_metadata: dict

Holdout metadata dict. See backtest/holdout metadata info in Notes for more details.

backtest_statuses: list of dict

List of backtest statuses dict. The list index of status dict is the backtest index. See backtest/holdout status info in Notes for more details.

holdout_statuses: dict

Holdout status dict. See backtest/holdout status info in Notes for more details.

class datarobot.models.datetime_trend_plots.ForecastVsActualPlot(project_id, model_id, forecast_distances, start_date, end_date, resolution, bins, calendar_events)

Forecast vs Actual plot for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

• actual: float or None

  Average actual value of the target in the bin. None if there are no entries in the bin.

• forecasts: list of float

  A list of average forecasts for the model for each forecast distance. Empty if there are no forecasts in the bin. Each index in the forecasts list maps to forecastDistances list index.

• error: float or None

  Average absolute residual value of the bin. None if there are no entries in the bin.

• normalized_error: float or None

  Normalized average absolute residual value of the bin. None if there are no entries in the bin.

• frequency: int or None

  Indicates number of values averaged in bin.

Calendar event is a dict containing the following:

• name: string

  Name of the calendar event.

• date: datetime

  Date of the calendar event.

• series_id: string or None

  The series ID for the event. If this event does not specify a series ID, then this will be None, indicating that the event applies to all series.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

forecast_distances: list of int

A list of forecast distances that were retrieved.

resolution: string

The resolution that is used for binning. One of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.

calendar_events: list of dict

List of calendar events for the plot. See calendar events info in Notes for more details.

class datarobot.models.datetime_trend_plots.ForecastVsActualPlotPreview(project_id, model_id, start_date, end_date, bins)

Forecast vs Actual plot preview for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

• actual: float or None

  Average actual value of the target in the bin. None if there are no entries in the bin.

• predicted: float or None

  Average prediction of the model in the bin. None if there are no entries in the bin.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.

class datarobot.models.datetime_trend_plots.AnomalyOverTimePlotsMetadata(project_id, model_id, resolutions, backtest_metadata, holdout_metadata, backtest_statuses, holdout_statuses)

Anomaly over Time metadata for datetime model.

Added in version v2.25.

Notes

Backtest/holdout status is a dict containing the following:

• training: string

  Status backtest/holdout training. One of datarobot.enums.DATETIME_TREND_PLOTS_STATUS

• validation: string

  Status backtest/holdout validation. One of datarobot.enums.DATETIME_TREND_PLOTS_STATUS

Backtest/holdout metadata is a dict containing the following:

• training: dict

  Start and end dates for the backtest/holdout training.

• validation: dict

  Start and end dates for the backtest/holdout validation.

Each dict in the training and validation in backtest/holdout metadata is structured like:

• start_date: datetime.datetime or None

  The datetime of the start of the chart data (inclusive). None if chart data is not computed.

• end_date: datetime.datetime or None

  The datetime of the end of the chart data (exclusive). None if chart data is not computed.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

resolutions: list of string

A list of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION, which represents available time resolutions for which plots can be retrieved.

backtest_metadata: list of dict

List of backtest metadata dicts. The list index of metadata dict is the backtest index. See backtest/holdout metadata info in Notes for more details.

holdout_metadata: dict

Holdout metadata dict. See backtest/holdout metadata info in Notes for more details.

backtest_statuses: list of dict

List of backtest statuses dict. The list index of status dict is the backtest index. See backtest/holdout status info in Notes for more details.

holdout_statuses: dict

Holdout status dict. See backtest/holdout status info in Notes for more details.

class datarobot.models.datetime_trend_plots.AnomalyOverTimePlot(project_id, model_id, start_date, end_date, resolution, bins, calendar_events)

Anomaly over Time plot for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

• predicted: float or None

  Average prediction of the model in the bin. None if there are no entries in the bin.

• frequency: int or None

  Indicates number of values averaged in bin.

Calendar event is a dict containing the following:

• name: string

  Name of the calendar event.

• date: datetime

  Date of the calendar event.

• series_id: string or None

  The series ID for the event. If this event does not specify a series ID, then this will be None, indicating that the event applies to all series.

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

resolution: string

The resolution that is used for binning. One of datarobot.enums.DATETIME_TREND_PLOTS_RESOLUTION

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.

calendar_events: list of dict

List of calendar events for the plot. See calendar events info in Notes for more details.

class datarobot.models.datetime_trend_plots.AnomalyOverTimePlotPreview(project_id, model_id, prediction_threshold, start_date, end_date, bins)

Anomaly over Time plot preview for datetime model.

Added in version v2.25.

Notes

Bin is a dict containing the following:

• start_date: datetime.datetime

  The datetime of the start of the bin (inclusive).

• end_date: datetime.datetime

  The datetime of the end of the bin (exclusive).

Attributes:

project_id: string

The project ID.

model_id: string

The model ID.

prediction_threshold: float

Only bins with predictions exceeding this threshold are returned in the response.

start_date: datetime.datetime

The datetime of the start of the chart data (inclusive).

end_date: datetime.datetime

The datetime of the end of the chart data (exclusive).

bins: list of dict

List of plot bins. See bin info in Notes for more details.