Transformer

RandomIntervals

Random interval feature transformer.

Extracts intervals with random length, position and dimension from series in fit. Transforms each interval subseries using the given transformer(s) and concatenates them into a feature vector in transform.

Currently, the transform is re-fit for every interval in transform. As such, it may not be suitable for some supervised transformers in its current state.

Schnellstart

python

from sktime.transformations.random_intervals import RandomIntervals

estimator = RandomIntervals(n_intervals=100, transformers=None, random_state=None, n_jobs=1)

Parameter(4)

n_intervalsint, default=100,: The number of intervals of random length, position and dimension to be extracted.
transformerstransformer or list of transformers, default=None,: Transformer(s) used to extract features from each interval. If None, defaults to the SummaryTransformer using [mean, median, min, max, std, 25% quantile, 75% quantile]
n_jobsint, default=1: The number of jobs to run in parallel for both fit and predict. -1 means using all processors.
random_stateint or None, default=None: Seed for random, integer.