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Next: .EN .TH C4.5 1 .SH NAME .PP consult \- classify items using a decision tree .SH SYNOPSIS .PP .B consult [ \fB-f\fR FNS ] [ \fB-t\fR ] .SH DESCRIPTION .PP .I Consult reads a decision tree produced by c4.5 and uses this to classify items whose descr
From: Simplane Simple Plane Simulate Plain Simple on 9 Jun 2010 19:03
..EN
..TH C4.5 1
..SH NAME
..PP
c4.5rules \- form production rules from unpruned decision trees
..SH SYNOPSIS
..PP
..B c4.5rules
[ \fB-f\fR filestem ]
[ \fB-u\fR ]
[ \fB-v\fR verb ]
[ \fB-F\fR siglevel ]
[ \fB-c\fR cf ]
[ \fB-r\fR redundancy ]
..SH DESCRIPTION
..PP
..I C4.5rules
reads the decision tree or trees produced by C4.5 and generates
a set of production rules from each tree and
from all trees together.
All files read and written by C4.5 are of the form
..I filestem.ext
where
..I filestem
is a file name stem that identifies the induction task and
..I ext
is an extension that defines the type of file.
The Rules program
expects to find a
..B names file
defining class, attribute and attribute value names, a
..B data file
containing a set of objects whose class and value of each
attribute is specified, a
..B unpruned file
generated by C4.5 from the
..B data file,
and (optionally) a
..B test file
containing unseen objects.
..PP
For each tree that it finds, the program generates a set of
pruned rules, and then sifts this set in an attempt to find
the most useful subset of them. If more than one tree was
found, all subsets are then merged and the resulting composite
set of rules is then sifted. The final set of rules is saved
in a machine-readable format in a
..B rules
file.
Each of the rulesets produced is then evaluated on the
original training data and (optionally) on the test data.
..PP
..SH OPTIONS
..PP
..TP 12
..BI \-f filestem\^
Specify the filename stem (default
..B DF).
..TP
..B \-u
Evaluate rulesets on unseen cases in file
..I filestem.test.
..TP
..BI \-v verb\^
Set the verbosity level [0-3] (default 0).
..TP
..BI \-F siglevel\^
Invoke Fisher's significance test when pruning rules.
If a rule contains a condition whose probability of being irrelevant
is greater than the stated level, the rule is pruned further
(default: no significance testing).
..TP
..BI \-c cf\^
Set the confidence level used in forming the pessimistic
estimate of a rule's error rate (default 25%).
..TP
..BI \-r redundancy\^
If many irrelevant or redundant attributes are included, estimate
the ratio of attributes to ``sensible'' attributes (default 1).
..PP
..SH FILES
..PP
..in 8
c4.5
..br
c4.5rules
..br
filestem.data
..br
filestem.names
..br
filestem.unpruned (unpruned trees)
..br
filestem.rules (production rules)
..br
filestem.test (unseen data)
..in 0
..PP
..SH SEE ALSO
..PP
c4.5(1), consultr(1)
..SH BUGS
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Prev: "NO BOX CONTAINS THE BOX NUMBERS THAT DON'T CONTAIN THEIR OWN BOX NUMBER" ~ XEN
Next: .EN .TH C4.5 1 .SH NAME .PP consult \- classify items using a decision tree .SH SYNOPSIS .PP .B consult [ \fB-f\fR FNS ] [ \fB-t\fR ] .SH DESCRIPTION .PP .I Consult reads a decision tree produced by c4.5 and uses this to classify items whose descr