This help file contains a description of the format of class logregtree.
logregtree()An object of class logregtree is typically a substructure of an object
of the class logregmodel. It will typically be the result of
using the fitting function logreg. An object of class
logictree has the following components:
the sequence number of the current tree within the model.
the coefficients of this tree.
a matrix (data.frame) with five columns; see below for the format.
Ingo Ruczinski ingo@jhu.edu and Charles Kooperberg clk@fredhutch.org.
When storing trees, we number the location of the nodes using the following scheme (this is an example for a tree with at most 8 terminal nodes, but the generalization should be obvious):
| 1 | ||||||||||||||
| 2 | 3 | |||||||||||||
| 4 | 5 | 6 | 7 | |||||||||||
| 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 |
Each node may or may not be present in the current tree. If it is present, it can contain an operator (``and'' or ``or''), in which case it has to child nodes, or it can contain a variable, in which case the node is a terminal node. It is also possible that the node does not exist (as the user only specifies the maximum tree size, not the tree size that is actually fitted).
Output files have one line for each node. Each line contains 5 numbers:
the node number.
does this node contain an ``and'' (1), an ``or'' (2), a variable (3), or is the node empty (0).
if the node contains a variable, which one is it; e.g. if this number is 3 the node contains X3.
if the node contains a variable, does it contain the regular variable (0) or its complement (1)
is the node empty (0) or not (1) (this information is redundant with the second number)
Example
| AND | ||||||||||||||
| OR | OR | |||||||||||||
| OR | OR | X20 | OR | |||||||||||
| X17 | X12 | X3 | X13c | X2 | X1 |
is represented as
| 1 | 1 | 0 | 0 | 1 |
| 2 | 2 | 0 | 0 | 1 |
| 3 | 2 | 0 | 0 | 1 |
| 4 | 2 | 0 | 0 | 1 |
| 5 | 2 | 0 | 0 | 1 |
| 6 | 3 | 20 | 0 | 1 |
| 7 | 2 | 0 | 0 | 1 |
| 8 | 3 | 17 | 0 | 1 |
| 9 | 3 | 12 | 0 | 1 |
| 10 | 3 | 3 | 0 | 1 |
| 11 | 3 | 13 | 1 | 1 |
| 12 | 0 | 0 | 0 | 0 |
| 13 | 0 | 0 | 0 | 0 |
| 14 | 3 | 2 | 0 | 1 |
| 15 | 3 | 1 | 0 | 1 |
Ruczinski I, Kooperberg C, LeBlanc ML (2003). Logic Regression, Journal of Computational and Graphical Statistics, 12, 475-511.
Ruczinski I, Kooperberg C, LeBlanc ML (2002). Logic Regression - methods and software. Proceedings of the MSRI workshop on Nonlinear Estimation and Classification (Eds: D. Denison, M. Hansen, C. Holmes, B. Mallick, B. Yu), Springer: New York, 333-344.
Selected chapters from the dissertation of Ingo Ruczinski, available from https://research.fredhutch.org/content/dam/stripe/kooperberg/ingophd-logic.pdf
logreg,
plot.logregtree,
print.logregtree,
logregmodel
logregtree() # displays this help file
help(logregtree) # equivalent
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