method
active
method:sigmoid-fittingsigmoid fitting
Fitting accuracy-vs-shot curves with logistic functions to extract k50 and width.
Neighborhood — ranked by edge-count
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Fitting a logistic function to success probability as a function of S or shot count to estimate midpoints and widths.
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- Input from environment that the agent models and predicts.
- Fit a sigmoid to accuracy vs. k to estimate k50 and phase width.
- A core requirement of the inductive theory of mirror self-recognition, implemented by the self-prior's visual-proprioceptive associations
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- Single-layer neural network that computes weighted sum of inputs; can only represent linearly separable functions