pub struct AdvancedParallelKMeans { /* private fields */ }Expand description
Advanced-parallel K-means clustering
Implementations§
Source§impl AdvancedParallelKMeans
impl AdvancedParallelKMeans
Sourcepub fn new(k: usize, config: WorkStealingConfig) -> SpatialResult<Self>
pub fn new(k: usize, config: WorkStealingConfig) -> SpatialResult<Self>
Create a new advanced-parallel K-means clusterer
Sourcepub fn fit_parallel(
&self,
points: &ArrayView2<'_, f64>,
) -> SpatialResult<(Array2<f64>, Array1<usize>)>
pub fn fit_parallel( &self, points: &ArrayView2<'_, f64>, ) -> SpatialResult<(Array2<f64>, Array1<usize>)>
Perform K-means clustering (Lloyd’s algorithm) on the given points.
This runs a genuine K-means: deterministic k-means++ seeding followed by alternating assignment / centroid-update iterations until the assignments stop changing or a maximum iteration count is reached. Distance computations use the hardware-optimized SIMD kernels.
§Returns
A tuple (centroids, assignments) where centroids has shape
(k, n_dims) and assignments[i] is the cluster index of point i.
Auto Trait Implementations§
impl !RefUnwindSafe for AdvancedParallelKMeans
impl !UnwindSafe for AdvancedParallelKMeans
impl Freeze for AdvancedParallelKMeans
impl Send for AdvancedParallelKMeans
impl Sync for AdvancedParallelKMeans
impl Unpin for AdvancedParallelKMeans
impl UnsafeUnpin for AdvancedParallelKMeans
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