Struct HeterogeneousGraphLearning 

pub struct HeterogeneousGraphLearning {
    pub node_types: Vec<String>,
    pub edge_types: Vec<(String, String)>,
    pub edge_weights: HashMap<(String, String), f64>,
    pub embedding_dims: HashMap<String, usize>,
    pub k_neighbors: HashMap<(String, String), usize>,
    pub random_state: Option<u64>,
}

Heterogeneous graph learning for mixed data types

Fields

node_types: Vec<String>

Node types in the heterogeneous graph

edge_types: Vec<(String, String)>

Edge types connecting different node types

edge_weights: HashMap<(String, String), f64>

Weights for different edge types

embedding_dims: HashMap<String, usize>

Embedding dimensions for each node type

k_neighbors: HashMap<(String, String), usize>

Number of neighbors for each edge type

random_state: Option<u64>

Random state for reproducibility

Implementations

impl HeterogeneousGraphLearning

pub fn new() -> Self

Create a new heterogeneous graph learning instance

pub fn node_types(self, types: Vec<String>) -> Self

Set node types

pub fn edge_types(self, types: Vec<(String, String)>) -> Self

Set edge types

pub fn edge_weights(self, weights: HashMap<(String, String), f64>) -> Self

Set weights for edge types

pub fn embedding_dims(self, dims: HashMap<String, usize>) -> Self

Set embedding dimensions for node types

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

Set random state

pub fn fit( &self, data: &HashMap<String, ArrayView2<'_, f64>>, ) -> Result<HashMap<String, Array2<f64>>, SklearsError>

Learn embeddings for heterogeneous graph

Trait Implementations

impl Clone for HeterogeneousGraphLearning

fn clone(&self) -> HeterogeneousGraphLearning

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Default for HeterogeneousGraphLearning

fn default() -> Self

Returns the “default value” for a type.