DAGMiningResult
DAGMiningResult(chains, diversity, parent_child_edges, n_components)Result of DAG mining on an embedding space.
DAG mining finds hierarchical structures by using neighbor diversity as a generality signal. Points with diverse neighbors (connecting many topics) are considered “general”, while points with coherent neighbors (tight clusters) are “specific”.
Attributes
| Name | Type | Description |
|---|---|---|
| chains | List[DAGChain] | List of extracted DAG chains |
| diversity | np.ndarray | Neighbor diversity score for each point |
| parent_child_edges | List[Tuple[int, int, float, float]] | List of (parent, child, similarity, gap) tuples |
| n_components | int | Number of connected components in the DAG |
Methods
| Name | Description |
|---|---|
| get_chains_by_coherence | Return chains with at least min_coherence. |
| get_chains_by_length | Return chains with at least min_length nodes. |
| summary | Return summary statistics. |
get_chains_by_coherence
DAGMiningResult.get_chains_by_coherence(min_coherence=0.65)Return chains with at least min_coherence.
get_chains_by_length
DAGMiningResult.get_chains_by_length(min_length=3)Return chains with at least min_length nodes.
summary
DAGMiningResult.summary()Return summary statistics.