# applied(to:eventHandler:) Performs a prediction on a shaped array of features. ``` func applied(to input: MLShapedArray, eventHandler: EventHandler? = nil) async throws -> MLShapedArray ``` ## Parameters `input` An shaped array of features. The shape must be `[N, featureSize]` where `N` is the length of the sequence, which must be at least `inputWindowSize`. `eventHandler` An event handler. ## Return Value A shaped array of predictions with shape `[M, forecastWindowSize, annotationSize]` where `M` is the number of predictions based on the input sequence length and the [`stride`](/documentation/CreateMLComponents/LinearTimeSeriesForecaster/Model/stride) property. ## Discussion This method uses a sliding window to chunk the input features into [`inputWindowSize`](/documentation/CreateMLComponents/LinearTimeSeriesForecaster/Model/inputWindowSize) elements every [`stride`](/documentation/CreateMLComponents/LinearTimeSeriesForecaster/Model/stride) elements. If you want to use a different windowing strategy, use [`applied(toWindow:eventHandler:)`](/documentation/CreateMLComponents/LinearTimeSeriesForecaster/Model/applied(toWindow:eventHandler:)). --- Copyright © 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)