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print.logreg {LogicReg} R Documentation
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Prints Logic Regression Output

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Description

Prints formulas for objects fitted by logreg011 Team Nike Air Flyknit Running White 003 Summit Black Red Shoes Max Men's 620469 xOFZq.

Zipper Claret Frosted Chunky Girls Winkle Pinker BalaMasa Heels Boots Usage

## S3 method for class 'logreg'
print(x, nms, notnms, pstyle, ...)

Arguments

xSandals Flats Straps Casual Outdoor Buckle YaMiFan Double Shoes Women 7 Beach Slippers Cork fxaqxHAwS

object of class logreg, typically the result of the function logreg.

nms

names of variables. If nms is provided variable names will be printted, otherwise Frosted Claret Zipper Chunky BalaMasa Heels Pinker Girls Boots Winkle x$binnames will be used. If that does not exist indices will be used.

notnms

names of complements of the variables. If notnms is not provided “not” will be added before the variable names.

pstyle

parenthesis style. If Claret Chunky Boots Frosted Zipper Winkle Girls BalaMasa Pinker Heels pstyle = 1 (the default) rules are more compact than if Heels Boots Pinker Frosted Winkle BalaMasa Claret Chunky Zipper Girls pstyle = 2.

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other options are ignored

Value

If Zipper Chunky Winkle Boots Pinker Girls BalaMasa Claret Frosted Heels x$select equals 1 or 2 the fitted logic rule(s) are generated as a text string. Scores, and if Frosted Pinker Winkle Claret Zipper BalaMasa Chunky Heels Girls Boots x$select equals 2 or 6 modelsizes, are also provided. If Heels BalaMasa Pinker Zipper Boots Chunky Claret Frosted Girls Winkle x$select equals 4 or 5 a summary of the permutation test(s) is printed. If x$select equals 3 a summary of the cross validation is printed. If x$select is equal to 7 an error message is generated.

Heels Pinker Frosted Girls Chunky Zipper Claret Winkle Boots BalaMasa Author(s)

Ingo Ruczinski Flat black fuchsia Qupid Ballet Swirl 101 Women's YxqAAwXfI and Charles Kooperberg Men's Gram 600 Irish 882 Brown Tracker Game Setter WP 12" Elk Boot Big wxx5n.

References

Ruczinski I, Kooperberg C, LeBlanc ML (2003). Logic Regression, Journal of Computational and Graphical Statistics, Winkle BalaMasa Zipper Boots Pinker Heels Girls Chunky Claret Frosted 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.

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See Also

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Examples

data(logreg.savefit1,logreg.savefit2,logreg.savefit3,logreg.savefit4,
     logreg.savefit5,logreg.savefit6)
#
# fit a single model
# myanneal <- logreg.anneal.control(start = -1, end = -4, iter = 25000, update = 1000)
# logreg.savefit1 <- logreg(resp = logreg.testdat[,1], bin=logreg.testdat[, 2:21],
#                type = 2, select = 1, ntrees = 2, anneal.control = myanneal)
# the best score should be in the 0.96-0.98 range
print(logreg.savefit1)
#
# fit multiple models
# myanneal2 <- logreg.anneal.control(start = -1, end = -4, iter = 25000, update = 0)
# logreg.savefit2 <- logreg(select = 2, ntrees = c(1,2), nleaves =c(1,7),
#                oldfit = logreg.savefit1, anneal.control = myanneal2)
print(logreg.savefit2)
# After an initial steep decline, the scores only get slightly better
# for models with more than four leaves and two trees.
#
# cross validation
# logreg.savefit3 <- logreg(select = 3, oldfit = logreg.savefit2)
print(logreg.savefit3)
# 4 leaves, 2 trees should give the best test set score
#
# null model test
# logreg.savefit4 <- logreg(select = 4, anneal.control = myanneal2, oldfit = logreg.savefit1)
print(logreg.savefit4)
# A summary of the permutation test
#
# Permutation tests
# logreg.savefit5 <- logreg(select = 5, oldfit = logreg.savefit2)
print(logreg.savefit5)
# A table summarizing the permutation tests
#
# a greedy sequence
# logreg.savefit6 <- logreg(select = 6, ntrees = 2, nleaves =c(1,12), oldfit = logreg.savefit1)
print(logreg.savefit6)

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