reservoir op• Data kinds: matrix × matrix → matrix
• Call: import fullseye as fs; fs.ledger.ridge_readout(X: 'Any', Y: 'Any', alpha: 'float' = 0.001) -> 'np.ndarray' (to call the implementation directly, import conngraph; conngraph.ridge_readout(X: 'Any', Y: 'Any', alpha: 'float' = 0.001) -> 'np.ndarray'; from the registry, opsconngraph.get("ridge_readout"))
> This operator's description has not been translated yet. The original text follows as it is.
リッジ回帰の読み出し重み (d+1, k) = (X̃ᵀX̃ + αI)⁻¹ X̃ᵀY、X̃ = [X, 1] (バイアス列を付ける)。
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• poc_larval_connectome_reservoir — py -3.11 examples/poc_larval_connectome_reservoir.py
matrix as input)reservoir_states · reservoir_encode · ridge_predict · graph_activation_latency · graph_activity_spread · points_activity_video · graph_layer_propagate · states_participation_ratio
reservoir)reservoir_from_graph · reservoir_states · reservoir_encode · ridge_predict
*Provenance: conngraph.py — CONNGRAPH operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.