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…ve reduction Rust engine, built from a pinned release tag of the public repository by install.sh (no vendored source or binaries); the build toolchain is removed from the image after the build. The scikit-learn wrapper shells out to the installed binary and satisfies the est / model() / max_time / random_state contract with sympy-compatible model strings in the data's feature names.
…nerated from main
…; remove clip predict, model() and complexity() now share a single SymPy expression built at fit time, so predict(X) matches evaluating model(est, X) wherever the expression is finite. The range clip is removed. The one remaining deviation is that rows where the expression is non-finite return the training mean so metric computation stays defined. The complexity() fallback now does a token-level operator count of the engine string instead of returning 0.
Add Keplearn: deterministic symbolic regression by best-first recursive reduction
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Some of the recent PRs had changes pushed to dev