KNeighborsRegressor
public class KNeighborsRegressor
K neighbors regressor.
The target is predicted by local interpolation of the targets associated of the nearest neighbors in the training set.
-
The order of the norm of the difference:
||a - b||_p
.Declaration
Swift
var p: Int
-
Weight function used in prediction.
Declaration
Swift
public var weights: String
-
Number of neighbors.
Declaration
Swift
var neighborCount: Int
-
The training data.
Declaration
Swift
var data: Tensor<Float>
-
The target value correspoing to training data.
Declaration
Swift
var labels: Tensor<Float>
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Create a K neighbors regressor model.
Declaration
Swift
public init( neighborCount: Int = 5, weights: String = "distance", p: Int = 2 )
Parameters
neighborCount
Number of neighbors to use, default to
5
.weights
Weight function used in prediction. Possible values
uniform
- uniform weighted,distance
- weight point by inverse of their distance. Default set todistance
.p
The order of the norm of the difference:
||a - b||_p
, default set to2
. -
Fit a K-neighbors regressor model.
Declaration
Swift
public func fit(data: Tensor<Float>, labels: Tensor<Float>)
Parameters
data
Training data with shape
[sample count, feature count]
.labels
Target value with shape
[sample count]
. -
Returns the average value of target.
Declaration
Swift
internal func computeWeights( distances: Tensor<Float>, labels: Tensor<Float> ) -> Tensor<Float>
Parameters
distances
Contains the distance between test data and top neighbors.
labels
Contains the value of target.
-
Returns the individual predicted value.
Declaration
Swift
internal func predictSingleSample(_ test: Tensor<Float>) -> Tensor<Float>
Parameters
data
Input data to be regressed.
Return Value
Predicted target value.
-
Returns predicted values.
Declaration
Swift
public func prediction(for data: Tensor<Float>) -> Tensor<Float>
Parameters
data
Test data with shape
[sample count, feature count]
.Return Value
Predicted value tensor.
-
Returns the coefficient of determination (
R^2
) of the prediction.Declaration
Swift
public func score(data: Tensor<Float>, labels: Tensor<Float>) -> Float
Parameters
data
Sample data with shape
[sample count, feature count]
.labels
Target values with shape
[sample count]
.Return Value
The coefficient of determination (
R^2
) of the prediction.