Module ml 

Machine learning utilities for graph neural networks.

Structs

DataSplit

Result of a data split.

DataSplitter

Data splitter for graph data.

FeatureNormalizer

Feature normalizer for graph features.

SplitConfig

Configuration for data splitting.

Enums

NormalizationMethod

Feature normalization method.

SplitStrategy

Strategy for splitting data.

Functions

compute_amount_features

Computes amount-based features.

compute_benford_features

Computes Benford’s law features for an amount.

compute_edge_direction_features

Computes edge direction features for directed graphs.

compute_structural_features

Computes structural features for nodes.

compute_temporal_features

Computes temporal features for edges.

label_encode

Label encodes a categorical value.

one_hot_encode

One-hot encodes a categorical value.

positional_encoding

Creates positional encoding for graph nodes (similar to transformer positional encoding).

sample_negative_edges

Creates negative edge samples for link prediction.