Struct DynamicGraphLearning 

pub struct DynamicGraphLearning {
    pub learning_rate: f64,
    pub forgetting_factor: f64,
    pub k_neighbors: usize,
    pub buffer_size: usize,
    pub edge_threshold: f64,
    pub max_nodes: Option<usize>,
    pub random_state: Option<u64>,
    /* private fields */
}

Dynamic graph learning for streaming and continuously evolving scenarios

Fields

learning_rate: f64

Learning rate for online updates

forgetting_factor: f64

Forgetting factor for old connections

k_neighbors: usize

Number of neighbors for new node integration

buffer_size: usize

Buffer size for streaming updates

edge_threshold: f64

Threshold for edge creation/removal

max_nodes: Option<usize>

Maximum number of nodes to maintain

random_state: Option<u64>

Random state for reproducibility

Implementations

impl DynamicGraphLearning

pub fn new() -> Self

Create a new dynamic graph learning instance

pub fn learning_rate(self, lr: f64) -> Self

Set the learning rate for online updates

pub fn forgetting_factor(self, factor: f64) -> Self

Set the forgetting factor for old connections

pub fn k_neighbors(self, k: usize) -> Self

Set the number of neighbors for new node integration

pub fn buffer_size(self, size: usize) -> Self

Set the buffer size for streaming updates

pub fn edge_threshold(self, threshold: f64) -> Self

Set the edge threshold for creation/removal

pub fn max_nodes(self, max_nodes: usize) -> Self

Set the maximum number of nodes to maintain

pub fn random_state(self, seed: u64) -> Self

Set the random state for reproducibility

pub fn initialize( &mut self, initial_features: ArrayView2<'_, f64>, ) -> Result<(), SklearsError>

Initialize the dynamic graph with initial data

pub fn add_nodes( &mut self, new_features: ArrayView2<'_, f64>, ) -> Result<(), SklearsError>

Add new nodes to the dynamic graph

pub fn update_node_features( &mut self, node_idx: usize, new_features: ArrayView1<'_, f64>, ) -> Result<(), SklearsError>

Update node features dynamically

pub fn get_adjacency_matrix(&self) -> Option<&Array2<f64>>

Get the current adjacency matrix

pub fn get_node_features(&self) -> Option<&Array2<f64>>

Get the current node features

pub fn get_recent_updates(&self, n_updates: usize) -> Vec<&GraphUpdate>

Get recent updates from the buffer

pub fn apply_temporal_decay(&mut self) -> Result<(), SklearsError>

Apply decay to all edges to simulate forgetting

pub fn get_statistics(&self) -> HashMap<String, f64>

Get graph statistics

Trait Implementations

impl Clone for DynamicGraphLearning

fn clone(&self) -> DynamicGraphLearning

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Default for DynamicGraphLearning

fn default() -> Self

Returns the “default value” for a type.