---
title: "init(validation:batchSize:maximumIterations:predictionWindowSize:augmentationOptions:algorithm:targetFrameRate:)"
framework: createml
role: symbol
role_heading: Initializer
path: "createml/mlhandactionclassifier/modelparameters-swift.struct/init(validation:batchsize:maximumiterations:predictionwindowsize:augmentationoptions:algorithm:targetframerate:)"
---

# init(validation:batchSize:maximumIterations:predictionWindowSize:augmentationOptions:algorithm:targetFrameRate:)

Creates a set of training session parameters for a hand action classifier task.

## Declaration

```swift
init(validation: MLHandActionClassifier.ModelParameters.ValidationData = .split(strategy: .automatic), batchSize: Int = MLHandActionClassifier.__Defaults.batchSize, maximumIterations: Int = MLHandActionClassifier.__Defaults.maximumIterations, predictionWindowSize: Int = MLHandActionClassifier.__Defaults.predictionWindowSize, augmentationOptions: MLHandActionClassifier.VideoAugmentationOptions = [], algorithm: MLHandActionClassifier.ModelParameters.ModelAlgorithmType = .gcn, targetFrameRate: Double = MLHandActionClassifier.__Defaults.targetFrameRate)
```

## Discussion

Discussion validation: An MLHandActionClassifier.ModelParameters.ValidationData instance. batchSize: The number of videos the training session uses for each of its training iterations. maximumIterations: The largest number of training iterations the training session can use. predictionWindowSize: The number of frames the training session uses to train a hand action classifier. For example, set to 60 to capture hand actions that take 2 seconds from videos that have a frame rate of 30 frames per second. augmentationOptions: The variations the training session uses to add more variety to its training dataset. algorithm: The algorithm the training session uses to train the hand action classifier. targetFrameRate: The number of frames the training session uses per second of video to train a hand action classifier.