# `Drift`

### *class* capymoa.stream.drift.Drift[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/drift.py#L793)

Bases: [`object`](https://docs.python.org/3/builtins/functions.html#object)

Represents a concept drift in a DriftStream. See 2.7.1 Concept drift framework in <sup>[1](#id2)</sup>.

* <a id='id2'>**[1]**</a> Bifet, Albert, et al. “Data stream mining: a practical approach.” COSI (2011).

#### \_\_init_\_(position, width=0, \*, random_seed=1)[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/stream/drift.py#L799)

Construct a drift in a DriftStream.

* **Parameters:**
  * **position** – The location of the drift in terms of the number of instances processed prior to it occurring.
  * **width** – The size of the window of change. A width of 0 or 1 corresponds to an abrupt drift.
  * **random_seed** – Seed for random number generation, defaults to 1.
    Keyword-only, so a leftover positional argument from the removed
    `alpha` parameter fails at the call site rather than silently
    becoming the seed.