---
title: "BNNSCreateNearestNeighbors(_:_:_:_:_:)"
framework: accelerate
role: symbol
role_heading: Function
path: "accelerate/bnnscreatenearestneighbors(_:_:_:_:_:)"
---

# BNNSCreateNearestNeighbors(_:_:_:_:_:)

Returns a new k-nearest neighbors object.

## Declaration

```swift
func BNNSCreateNearestNeighbors(_ max_n_samples: UInt32, _ n_features: UInt32, _ n_neighbors: UInt32, _ data_type: BNNSDataType, _ filter_params: UnsafePointer<BNNSFilterParameters>?) -> BNNSNearestNeighbors?
```

## Parameters

- `max_n_samples`: The maximum number of data points.
- `n_features`: The number of features or dimensions of each data point.
- `n_neighbors`: The number of nearest neighbors that a subsequent call to doc://com.apple.accelerate/documentation/Accelerate/BNNSNearestNeighborsGetInfo(_:_:_:_:) calculates.
- `data_type`: The data type of the data points. This must be either BNNSDataTypeFloat32 or BNNSDataTypeFloat16.
- `filter_params`: The filter runtime parameters.

## Return Value

Return Value A new k-nearest neighbors object, or nil if the operation failed.

## Discussion

Discussion The following code generates eight 2D data points and loads them into a k-nearest neighbors object with a single call to the BNNSNearestNeighborsLoad(_:_:_:) function. The code then computes the four nearest neighbors, based on Euclidean distance, to the sample data point at index 7 of the samples data. let samples: [Float] = [     1, 2,   // 0     7, 2,   // 1     3, 4,   // 2     8, 4,   // 3     3, 7,   // 4     7, 7,   // 5     2, 8,   // 6     2, 5    // 7 ]

let maximumSampleCount: UInt32 = 8 let dimensionCount: UInt32 = 2 let nearestNeighborCount: UInt32 = 4

let knn = BNNSCreateNearestNeighbors(     maximumSampleCount,     dimensionCount,     nearestNeighborCount,     BNNSDataType.float,     nil)

defer {     BNNSDestroyNearestNeighbors(knn) }

BNNSNearestNeighborsLoad(     knn,     UInt32(samples.count) / dimensionCount,     samples)

var indices = [Int32](repeating: 0,                       count: Int(nearestNeighborCount)) var distances = [Float](repeating: 0,                         count: Int(nearestNeighborCount))

let sampleDataPointIndex = 7 BNNSNearestNeighborsGetInfo(     knn,     Int32(sampleDataPointIndex),     &indices,     &distances) On return, the indices array contains the values [7, 2, 4, 6] and the distances array contains the values [0.0, 1.4142135, 2.236068, 3.0].

## See Also

### K-nearest neighbors calculation

- [BNNS.NearestNeighbors](accelerate/bnns/nearestneighbors.md)
- [BNNSNearestNeighbors](accelerate/bnnsnearestneighbors.md)
- [BNNSNearestNeighborsLoad(_:_:_:)](accelerate/bnnsnearestneighborsload(_:_:_:).md)
- [BNNSNearestNeighborsGetInfo(_:_:_:_:)](accelerate/bnnsnearestneighborsgetinfo(_:_:_:_:).md)
- [BNNSDestroyNearestNeighbors(_:)](accelerate/bnnsdestroynearestneighbors(_:).md)