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Some inducers are still being developed or have esoteric uses. We
briefly mention them.
- Accuracy estimator
- is a wrapper inducer that runs a given
inducer in ACC_INDUCER, estimates its accuracy using an accuracy
estimation method, and returns that as the resulting accuracy.
The
AccEst utility provides a friendlier interface, but there are
occasions where one wants to do two levels of accuracy estimation
( e.g.
, cross-validation accuracy on holdout sets), where this
inducer is very useful [].
- NULL
- always predicts unknown and thus gets 0% accuracy. It
is mostly used internally, but can be used with the Inducer utility
and DISP_CONFUSION_MAT set to true in order to view the
distribution of the labels. The ``info'' utility is probably a better
way of getting basic statistics about a data file.
- EODG
- is an inducer for building oblivious decision graphs top-down
[]. Cannot handle unknown values.
- LazyDT
- is a lazy decision tree algorithm, described in
friedman-kohavi-yun-lazydt.
- Order-fss
- searches for an attribute ordering. Very researchy.
- Disc-search
- is a wrapper discretizer that searches for the best
number of intervals for each attribute. Very slow.
- Weight-search
- is a wrapper discretizer that searches for the
best weight for each attribute (from a uniform set of weights).
Slow. Researchy. Not much improvement over feature subset
selection.
- CatDT
- Builds decision trees with categorizers you choose at
the leaves. Researchy. Requires that inducers support copies,
which very few do ( e.g.
, naive-bayes).
Ronny Kohavi
Sun Oct 6 23:17:50 PDT 1996