Ensemble scikit-learn aggregator¶
Aggregator wrapped around the Ensemble model of sklearn. `sklearn https://scikit-learn.org/stable/modules/ensemble.html`_.
- class darts.ad.aggregators.ensemble_sklearn_aggregator.EnsembleSklearnAggregator(model)[source]¶
Bases:
darts.ad.aggregators.aggregators.FittableAggregator
Methods
eval_accuracy
(actual_anomalies, series[, ...])Aggregates the (sequence of) multivariate series given as input into one (sequence of) series and evaluates the results against true anomalies.
fit
(actual_anomalies, series)Fit the aggregators on the (sequence of) multivariate binary series.
predict
(series)Aggregates the (sequence of) multivariate binary series given as input into a (sequence of) univariate binary series.
- eval_accuracy(actual_anomalies, series, window=1, metric='recall')¶
Aggregates the (sequence of) multivariate series given as input into one (sequence of) series and evaluates the results against true anomalies.
- Parameters
actual_anomalies (
Sequence
[TimeSeries
]) – The (sequence of) ground truth of the anomalies (1 if it is an anomaly and 0 if not)series (
Sequence
[TimeSeries
]) – The (sequence of) multivariate binary series to aggregatewindow (
int
) – (Sequence of) integer value indicating the number of past samples each point represents in the (sequence of) series. The parameter will be used by the function_window_adjustment_anomalies()
in darts.ad.utils to transform actual_anomalies.metric (
str
) – Metric function to use. Must be one of “recall”, “precision”, “f1”, and “accuracy”. Default: “recall”
- Returns
(Sequence of) score for the (sequence of) series
- Return type
Union[float, Sequence[float]]
- fit(actual_anomalies, series)¶
Fit the aggregators on the (sequence of) multivariate binary series.
If a list of series is given, they must have the same number of components.
- Parameters
actual_anomalies (
Union
[TimeSeries
,Sequence
[TimeSeries
]]) – The (sequence of) ground truth of the anomalies (1 if it is an anomaly and 0 if not)series (
Union
[TimeSeries
,Sequence
[TimeSeries
]]) – The (sequence of) multivariate binary series
- predict(series)¶
Aggregates the (sequence of) multivariate binary series given as input into a (sequence of) univariate binary series.
- Parameters
series (
Union
[TimeSeries
,Sequence
[TimeSeries
]]) – The (sequence of) multivariate binary series to aggregate- Returns
(Sequence of) aggregated results
- Return type