ridge_predict — CONNGRAPH reservoir op

• Data kinds: matrix × matrix → matrix

• Call: import fullseye as fs; fs.ledger.ridge_predict(X: 'Any', Wout: 'Any') -> 'np.ndarray' (to call the implementation directly, import conngraph; conngraph.ridge_predict(X: 'Any', Wout: 'Any') -> 'np.ndarray'; from the registry, opsconngraph.get("ridge_predict"))

Usage

Prediction with the readout weights (T, k) = [X, 1] · Wout. Wout is the (d+1, k) from ridge_readout.

Detailed usage guide

• conngraph family guide

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• poc_larval_connectome_reservoir — py -3.11 examples/poc_larval_connectome_reservoir.py

Ops the type connects to (they accept matrix as input)

reservoir_states · reservoir_encode · ridge_readout · graph_activation_latency · graph_activity_spread · points_activity_video · graph_layer_propagate · states_participation_ratio

Same category (reservoir)

reservoir_from_graph · reservoir_states · reservoir_encode · ridge_readout

*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.