Struct TimeSeriesClusterer 

pub struct TimeSeriesClusterer {
    pub random_seed: Option<u64>,
    /* private fields */
}

Main struct for time series clustering and classification

Fields

random_seed: Option<u64>

Random seed for reproducibility

Implementations

impl TimeSeriesClusterer

pub fn new() -> Self

Create a new time series clusterer

pub fn with_seed(seed: u64) -> Self

Create a new clusterer with random seed

pub fn kmeans_clustering( &self, data: &Array2<f64>, config: &KMeansConfig, ) -> ClusteringResult<TimeSeriesClusteringResult>

Perform k-means clustering on time series data

Arguments

• data - Matrix where each row is a time series
• config - Configuration for k-means clustering

Returns

Result containing clustering results and statistics

pub fn hierarchical_clustering( &self, data: &Array2<f64>, config: &HierarchicalConfig, ) -> ClusteringResult<TimeSeriesClusteringResult>

Perform hierarchical clustering on time series data

Arguments

• data - Matrix where each row is a time series
• config - Configuration for hierarchical clustering

Returns

Result containing clustering results and dendrogram information

pub fn dbscan_clustering( &self, data: &Array2<f64>, config: &DBSCANConfig, ) -> ClusteringResult<TimeSeriesClusteringResult>

Perform DBSCAN clustering on time series data

Arguments

• data - Matrix where each row is a time series
• config - Configuration for DBSCAN clustering

Returns

Result containing clustering results (noise points labeled as -1)

pub fn knn_classification( &self, train_data: &Array2<f64>, train_labels: &Array1<usize>, test_data: &Array2<f64>, config: &KNNConfig, ) -> ClusteringResult<TimeSeriesClassificationResult>

Perform k-NN classification on time series data

Arguments

• train_data - Training time series matrix
• train_labels - Training labels
• test_data - Test time series matrix
• config - Configuration for k-NN classification

Returns

Result containing classification predictions and confidence scores

pub fn discovershapelets( &self, data: &Array2<f64>, labels: &Array1<usize>, config: &ShapeletConfig, ) -> ClusteringResult<ShapeletResult>

Discover shapelets in time series data

Arguments

• data - Time series data matrix
• labels - Class labels for supervised shapelet discovery
• config - Configuration for shapelet discovery

Returns

Result containing discovered shapelets and their quality measures

Trait Implementations

impl Default for TimeSeriesClusterer

fn default() -> Self

Returns the “default value” for a type.