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| -rw-r--r-- | README.md | 17 |
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@@ -75,6 +75,23 @@ Parameter names may be different -- parameters that are present in other lines o Use `bin/analyze-log.py file1.txt file2.txt ...` for analysis. +## Model Types + +dfatool supports six types of performance models: + +* CART: Regression Trees +* DECART: Regression Trees with exclusively binary features/parameters +* XGB: Regression Forests +* LMT: Linear Model Trees +* RMT: Regression Model Trees +* Least-Squares Regression + +Least-Squares Regression is essentially a subset of RMT with just a single tree node. +LMT and RMT differ significantly, as LMT uses a learning algorithm that starts out with a DECART and uses bottom-up pruning to turn it into an LMT, whereas RMT build a DECART that only considers parameters that are not suitable for least-squares regression and then uses least-squares regression to find and fit leaf functions. + +By default, dfatool uses heuristics to determine whether it should generate a simple least-squares regression function or a fully-fledge RMT. +Use arguments (e.g. `--force-tree`) and environment variables (see below) to change which kinds of models it considers. + ## Dependencies Python 3.7 or newer with the following modules: |