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Armin Rauschenberger
joinet
Commits
ffa77bbb
Commit
ffa77bbb
authored
Jul 03, 2020
by
Armin Rauschenberger
Browse files
competing models
parent
43282c0c
Changes
10
Hide whitespace changes
Inline
Side-by-side
R/functions.R
View file @
ffa77bbb
...
...
@@ -530,8 +530,10 @@ print.joinet <- function(x,...){
cv.joinet
<-
function
(
Y
,
X
,
family
=
"gaussian"
,
nfolds.ext
=
5
,
nfolds.int
=
10
,
foldid.ext
=
NULL
,
foldid.int
=
NULL
,
type.measure
=
"deviance"
,
alpha.base
=
1
,
alpha.meta
=
1
,
compare
=
FALSE
,
mice
=
FALSE
,
cvpred
=
FALSE
,
times
=
FALSE
,
...
){
if
(
FALSE
){
fold
<-
foldid.ext
family
<-
"gaussian"
;
nfolds.ext
<-
5
;
nfolds.int
<-
10
;
foldid.ext
<-
foldid.int
<-
NULL
;
type.measure
<-
"deviance"
;
alpha.base
<-
alpha.meta
<-
1
;
mice
<-
cvpred
<-
times
<-
FALSE
#nfolds.ext <- 1; foldid.ext <- fold; nfolds.int <- 10; foldid.int <- NULL; compare <- TRUE
foldid.ext
<-
fold
;
nfolds.ext
<-
1
#nfolds.ext <- 1; nfolds.int <- 10; foldid.int <- NULL; compare <- TRUE
}
if
(
length
(
compare
)
==
1
&&
compare
==
TRUE
){
...
...
@@ -659,19 +661,28 @@ cv.joinet <- function(Y,X,family="gaussian",nfolds.ext=5,nfolds.int=10,foldid.ex
cat
(
"mars"
,
" "
)
start
<-
Sys.time
()
if
(
all
(
family
==
"gaussian"
)){
object
<-
earth
::
earth
(
x
=
X0
,
y
=
y0
)
# add:pmethod="cv"nfold=nfolds.int
object
<-
earth
::
earth
(
x
=
X0
,
y
=
y0
)
# equivalent: object <- mda::mars(x=X0,y=y0)
}
else
if
(
all
(
family
==
"binomial"
)){
object
<-
earth
::
earth
(
x
=
X0
,
y
=
y0
,
glm
=
list
(
family
=
stats
::
binomial
))
# add pmethod="cv",nfold=nfolds.int
object
<-
earth
::
earth
(
x
=
X0
,
y
=
y0
,
glm
=
list
(
family
=
stats
::
binomial
))
}
else
{
stop
(
"MARS requires either \"gaussian\" or \"binomial\" family."
,
call.
=
FALSE
)
}
# pmethod="cv" not available for multivariate outputs
## nk = min(200, max(20, 2 * ncol(x))) + 1
## nprune <- seq(from=2,to=nk,length.out=10)
### start trial ###
if
(
FALSE
){
#nk <- min(200, max(20, 2 * ncol(X0))) + 1
#nprune <- round(seq(from=2,to=nk,length.out=10))
#object <- list()
#for(j in seq_along(nprune)){
# object[[j]] <- earth::earth(x=X0,y=y0,nprune=nprune[j],pmethod="cv",nfold=nfolds.int)
#}
#sapply(object,function(x) x$gcv)
## i.e. run earth/mars with tryCatch for each nprune
## and select run with best cvm (here gcv)
# tune nprune (use default nk)!
}
pred
$
mars
[
foldid.ext
==
i
,]
<-
earth
:::
predict.earth
(
object
=
object
,
newdata
=
X1
,
type
=
"response"
)
end
<-
Sys.time
()
...
...
@@ -715,13 +726,17 @@ cv.joinet <- function(Y,X,family="gaussian",nfolds.ext=5,nfolds.int=10,foldid.ex
}
mean
<-
colMeans
(
y0
)
y0s
<-
y0
-
matrix
(
data
=
mean
,
nrow
=
nrow
(
X0
),
ncol
=
ncol
(
y0
),
byrow
=
TRUE
)
#lamL1.v <- exp(seq(from=log(10),to=log(20),length.out=11)) # original
lamL1.v
<-
seq
(
from
=
0
,
to
=
20
,
length.out
=
11
)
# trial
lamL2.v
<-
seq
(
from
=
0
,
to
=
5
,
length.out
=
11
)
lamL1.v
<-
lamL2.v
<-
exp
(
seq
(
from
=
0
,
to
=
5
,
length.out
=
11
))
cv
<-
remMap
::
remMap.CV
(
X
=
X0
,
Y
=
y0s
,
lamL1.v
=
lamL1.v
,
lamL2.v
=
lamL2.v
,
fold
=
nfolds.int
)
#graphics::plot(x=lamL1.v,y=log(as.numeric(cv$ols.cv[,3])))
index
<-
which
(
cv
$
ols.cv
==
min
(
cv
$
ols.cv
),
arr.ind
=
TRUE
)[
1
,]
object
<-
remMap
::
remMap
(
X.m
=
X0
,
Y.m
=
y0s
,
lamL1
=
lamL1.v
[
index
[
1
]],
lamL2
=
lamL2.v
[
index
[
2
]])
pick
<-
which.min
(
as.vector
(
cv
$
ols.cv
))
lamL1
<-
cv
$
l.index
[
1
,
pick
]
lamL2
<-
cv
$
l.index
[
2
,
pick
]
# index <- which(cv$ols.cv==min(cv$ols.cv),arr.ind=TRUE)[1,]
# rev(lamL1.v)[index[1]]
# rev(lamL2.v)[index[2]]
##cat("lam1:",lamL1,", lam2:",lamL2)
object
<-
remMap
::
remMap
(
X.m
=
X0
,
Y.m
=
y0s
,
lamL1
=
lamL1
,
lamL2
=
lamL2
)
pred
$
map
[
foldid.ext
==
i
,]
<-
matrix
(
data
=
mean
,
nrow
=
nrow
(
X1
),
ncol
=
ncol
(
y0
),
byrow
=
TRUE
)
+
X1
%*%
object
$
phi
end
<-
Sys.time
()
time
$
map
<-
as.numeric
(
difftime
(
end
,
start
,
units
=
"secs"
))
...
...
@@ -881,7 +896,7 @@ cv.joinet <- function(Y,X,family="gaussian",nfolds.ext=5,nfolds.int=10,foldid.ex
# now using cross-validation residual stacking (CVRS)
}
if
(
length
(
compare
)
>
1
){
cat
(
"\n"
)}
# was !is.null(compare)
if
(
is.character
(
compare
)){
cat
(
"\n"
)}
# --- development ---
...
...
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deleted
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>
vignette
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<h1
data-toc-skip
>
Multivariate Elastic Net Regression
</h1>
<small
class=
"dont-index"
>
Source:
<a
href=
"https://github.com/rauschenberger/joinet/blob/master/vignettes/article.Rmd"
><code>
vignettes/article.Rmd
</code></a></small>
<div
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><code>
article.Rmd
</code></div>
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<p>
The
<code>
joinet
</code>
manuscript is in preparation. Click
<a
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>
here
</a>
for the R package.
</p>
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Reference
</h2>
<p>
Armin Rauschenberger and Enrico Glaab (2020). “joinet: predicting correlated outcomes jointly to improve clinical prognosis”.
<em>
Manuscript in preparation.
</em></p>
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.
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Extract Coefficients
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Source:
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R/functions.R
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coef.joinet.Rd
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Extracts pooled coefficients.
(The meta learners linearly combines
the coefficients from the base learners.)
</p>
</div>
<pre
class=
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><span
class=
'co'
>
# S3 method for joinet
</span>
<span
class=
'fu'
><a
href=
'https://rdrr.io/r/stats/coef.html'
>
coef
</a></span>
(
<span
class=
'no'
>
object
</span>
,
<span
class=
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>
...
</span>
)
</pre>
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class=
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href=
"#arguments"
></a>
Arguments
</h2>
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class=
"ref-arguments"
>
<colgroup><col
class=
"name"
/><col
class=
"desc"
/></colgroup>
<tr>
<th>
object
</th>
<td><p><a
href=
'joinet.html'
>
joinet
</a>
object
</p></td>
</tr>
<tr>
<th>
...
</th>
<td><p>
further arguments (not applicable)
</p></td>
</tr>
</table>
<h2
class=
"hasAnchor"
id=
"value"
><a
class=
"anchor"
href=
"#value"
></a>
Value
</h2>
<p>
This function returns the pooled coefficients.
The slot
<code>
alpha
</code>
contains the intercepts
in a vector of length \(q\),
and the slot
<code>
beta
</code>
contains the slopes
in a matrix with \(p\) rows (inputs) and \(q\) columns.
</p>
<h2
class=
"hasAnchor"
id=
"examples"
><a
class=
"anchor"
href=
"#examples"
></a>
Examples
</h2>
<pre
class=
"examples"
><div
class=
'input'
><span
class=
'no'
>
n
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fu'
><a
href=
'https://rdrr.io/r/base/matrix.html'
>
matrix
</a></span>
(
<span
class=
'fu'
><a
href=
'https://rdrr.io/r/stats/Normal.html'
>
rnorm
</a></span>
(
<span
class=
'no'
>
n
</span>
*
<span
class=
'no'
>
p
</span>
),
<span
class=
'kw'
>
nrow
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
n
</span>
,
<span
class=
'kw'
>
ncol
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
p
</span>
)
<span
class=
'no'
>
Y
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fu'
><a
href=
'https://rdrr.io/r/base/lapply.html'
>
replicate
</a></span>
(
<span
class=
'kw'
>
n
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
q
</span>
,
<span
class=
'kw'
>
expr
</span><span
class=
'kw'
>
=
</span><span
class=
'fu'
><a
href=
'https://rdrr.io/r/stats/Normal.html'
>
rnorm
</a></span>
(
<span
class=
'kw'
>
n
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
n
</span>
,
<span
class=
'kw'
>
mean
</span><span
class=
'kw'
>
=
</span><span
class=
'fu'
><a
href=
'https://rdrr.io/r/base/colSums.html'
>
rowSums
</a></span>
(
<span
class=
'no'
>
X
</span>
[,
<span
class=
'fl'
>
1
</span>
:
<span
class=
'fl'
>
5
</span>
])))
<span
class=
'no'
>
object
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fu'
><a
href=
'joinet.html'
>
joinet
</a></span>
(
<span
class=
'kw'
>
Y
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
Y
</span>
,
<span
class=
'kw'
>
X
</span><span
class=
'kw'
>
=
</span><span
class=
'no'
>
X
</span>
)
<span
class=
'no'
>
coef
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fu'
><a
href=
'https://rdrr.io/r/stats/coef.html'
>
coef
</a></span>
(
<span
class=
'no'
>
object
</span>
)
</div></pre>
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