Assign observations with a fitted CUDA-aware k-means model

predict.cuda_kmeans() computes Euclidean distances to the fitted centres and returns either the closest-centre assignment or the complete distance matrix. Named features may be supplied in any order and are aligned safely.

Usage

# S3 method for class 'cuda_kmeans'
predict(
  object,
  newdata,
  type = c("cluster", "distance"),
  device = c("model", "auto", "cuda", "cpu"),
  ...
)

Arguments

object

A fitted cuda_kmeans object.

newdata

A finite numeric matrix or data frame with observations in rows and model features in columns. When omitted and type = "cluster", the training assignments in object$cluster are returned.

type

Return closest-centre "cluster" assignments or the observation-by-centre "distance" matrix.

device

Device used for the distance calculation. "model" reuses the fitted model's actual distance device; "auto", "cuda", and "cpu" follow the usual cudaverse device-selection rules.

...

Must be empty.

Value

For type = "cluster", an integer vector with observation names and, for recomputed assignments, stage-level provenance. For type = "distance", a numeric matrix whose columns identify the fitted centres. Omitting newdata returns validated stored training assignments unchanged and does not create a prediction stage.

See also

cuda_kmeans()

Examples

train <- as.matrix(iris[1:100, 1:4])
fit <- cuda_kmeans(train, centers = 3, seed = 1, device = "cpu")
predict(fit, as.matrix(iris[101:105, 1:4]), device = "cpu")
#> 101 102 103 104 105 
#>   1   1   1   1   1 
#> attr(,"device")
#> [1] "cpu"
#> attr(,"provenance_schema")
#> [1] "cudaverse-stage/1"
#> attr(,"requested_device")
#> [1] "cpu"
#> attr(,"compute_device")
#> [1] "cpu"
#> attr(,"compute_stages")
#> attr(,"compute_stages")$distance
#> $requested_device
#> [1] "cpu"
#> 
#> $device
#> [1] "cpu"
#> 
#> $backend
#> [1] "base"
#> 
#> $selection_reason
#> [1] "explicit_cpu"
#> 
#> $fallback
#> [1] FALSE
#> 
#> $output_device
#> [1] "cpu"
#> 
#> attr(,"class")
#> [1] "cuda_stage"
#> 
#> attr(,"compute_stages")$assignment
#> $requested_device
#> [1] "fixed-cpu"
#> 
#> $device
#> [1] "cpu"
#> 
#> $backend
#> [1] "base"
#> 
#> $selection_reason
#> [1] "algorithm_cpu_only"
#> 
#> $fallback
#> [1] FALSE
#> 
#> $output_device
#> [1] "cpu"
#> 
#> attr(,"class")
#> [1] "cuda_stage"
#> 
#> attr(,"backend")
#> [1] "base"
#> attr(,"parameters")
#> attr(,"parameters")$type
#> [1] "cluster"
#> 
#> attr(,"parameters")$metric
#> [1] "euclidean"
#> 
#> attr(,"source_device")
#> [1] "cpu"
#> attr(,"source_class")
#> [1] "matrix"