major change in the design of R interface
This commit is contained in:
unknown
parent
84e5fc285b
commit
0130be4acc
@ -3,16 +3,8 @@ importClassesFrom("Matrix", dgCMatrix, dgeMatrix)
|
||||
export(xgboost)
|
||||
export(xgb.DMatrix)
|
||||
export(xgb.getinfo)
|
||||
export(xgb.setinfo)
|
||||
|
||||
# exportClasses(xgb.Boost)
|
||||
exportMethods(predict)
|
||||
|
||||
# export(xgb.Booster)
|
||||
# export(xgb.train)
|
||||
# export(xgb.save)
|
||||
# export(xgb.predict)
|
||||
# export(xgb.dump)
|
||||
|
||||
|
||||
|
||||
export(xgb.train)
|
||||
export(xgb.save)
|
||||
export(xgb.load)
|
||||
export(xgb.dump)
|
||||
|
||||
@ -6,42 +6,6 @@
|
||||
library.dynam.unload("xgboost", libpath);
|
||||
}
|
||||
|
||||
# constructing DMatrix
|
||||
xgb.DMatrix <- function(data, info=list(), missing=0.0) {
|
||||
if (typeof(data) == "character") {
|
||||
handle <- .Call("XGDMatrixCreateFromFile_R", data, as.integer(FALSE), PACKAGE="xgboost")
|
||||
} else if(is.matrix(data)) {
|
||||
handle <- .Call("XGDMatrixCreateFromMat_R", data, missing, PACKAGE="xgboost")
|
||||
} else if(class(data) == "dgCMatrix") {
|
||||
handle <- .Call("XGDMatrixCreateFromCSC_R", data@p, data@i, data@x, PACKAGE="xgboost")
|
||||
} else {
|
||||
stop(paste("xgb.DMatrix: does not support to construct from ", typeof(data)))
|
||||
}
|
||||
dmat <- structure(handle, class="xgb.DMatrix")
|
||||
if (length(info) != 0) {
|
||||
for (i in 1:length(info)) {
|
||||
p <- info[i]
|
||||
xgb.setinfo(dmat, names(p), p[[1]])
|
||||
}
|
||||
}
|
||||
return(dmat)
|
||||
}
|
||||
# get information from dmatrix
|
||||
xgb.getinfo <- function(dmat, name) {
|
||||
if (typeof(name) != "character") {
|
||||
stop("xgb.getinfo: name must be character")
|
||||
}
|
||||
if (class(dmat) != "xgb.DMatrix") {
|
||||
stop("xgb.setinfo: first argument dtrain must be xgb.DMatrix");
|
||||
}
|
||||
if (name != "label" &&
|
||||
name != "weight" &&
|
||||
name != "base_margin" ) {
|
||||
stop(paste("xgb.getinfo: unknown info name", name))
|
||||
}
|
||||
ret <- .Call("XGDMatrixGetInfo_R", dmat, name, PACKAGE="xgboost")
|
||||
return(ret)
|
||||
}
|
||||
# set information into dmatrix, this mutate dmatrix
|
||||
xgb.setinfo <- function(dmat, name, info) {
|
||||
if (class(dmat) != "xgb.DMatrix") {
|
||||
@ -63,9 +27,10 @@ xgb.setinfo <- function(dmat, name, info) {
|
||||
.Call("XGDMatrixSetInfo_R", dmat, name, as.integer(info), PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
stop(pase("xgb.setinfo: unknown info name", name))
|
||||
stop(paste("xgb.setinfo: unknown info name", name))
|
||||
return(FALSE)
|
||||
}
|
||||
|
||||
# construct a Booster from cachelist
|
||||
xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
|
||||
if (typeof(cachelist) != "list") {
|
||||
@ -92,61 +57,9 @@ xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
|
||||
}
|
||||
return(structure(handle, class="xgb.Booster"))
|
||||
}
|
||||
# train a model using given parameters
|
||||
xgb.train <- function(params, dtrain, nrounds=10, watchlist=list(), obj=NULL, feval=NULL) {
|
||||
if (typeof(params) != "list") {
|
||||
stop("xgb.train: first argument params must be list");
|
||||
}
|
||||
if (class(dtrain) != "xgb.DMatrix") {
|
||||
stop("xgb.train: second argument dtrain must be xgb.DMatrix");
|
||||
}
|
||||
bst <- xgb.Booster(params, append(watchlist,dtrain))
|
||||
for (i in 1:nrounds) {
|
||||
if (is.null(obj)) {
|
||||
succ <- xgb.iter.update(bst, dtrain, i-1)
|
||||
} else {
|
||||
pred <- xgb.predict(bst, dtrain)
|
||||
gpair <- obj(pred, dtrain)
|
||||
succ <- xgb.iter.boost(bst, dtrain, gpair)
|
||||
}
|
||||
if (length(watchlist) != 0) {
|
||||
if (is.null(feval)) {
|
||||
msg <- xgb.iter.eval(bst, watchlist, i-1)
|
||||
cat(msg); cat("\n")
|
||||
} else {
|
||||
cat("["); cat(i); cat("]");
|
||||
for (j in 1:length(watchlist)) {
|
||||
w <- watchlist[j]
|
||||
if (length(names(w)) == 0) {
|
||||
stop("xgb.eval: name tag must be presented for every elements in watchlist")
|
||||
}
|
||||
ret <- feval(xgb.predict(bst, w[[1]]), w[[1]])
|
||||
cat("\t"); cat(names(w)); cat("-"); cat(ret$metric);
|
||||
cat(":"); cat(ret$value)
|
||||
}
|
||||
cat("\n")
|
||||
}
|
||||
}
|
||||
}
|
||||
return(bst)
|
||||
}
|
||||
# save model or DMatrix to file
|
||||
xgb.save <- function(handle, fname) {
|
||||
if (typeof(fname) != "character") {
|
||||
stop("xgb.save: fname must be character")
|
||||
}
|
||||
if (class(handle) == "xgb.Booster") {
|
||||
.Call("XGBoosterSaveModel_R", handle, fname, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
if (class(handle) == "xgb.DMatrix") {
|
||||
.Call("XGDMatrixSaveBinary_R", handle, fname, as.integer(FALSE), PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
stop("xgb.save: the input must be either xgb.DMatrix or xgb.Booster")
|
||||
return(FALSE)
|
||||
}
|
||||
# predict
|
||||
|
||||
|
||||
# predict, depreciated
|
||||
xgb.predict <- function(booster, dmat, outputmargin = FALSE) {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
stop("xgb.predict: first argument must be type xgb.Booster")
|
||||
@ -157,21 +70,12 @@ xgb.predict <- function(booster, dmat, outputmargin = FALSE) {
|
||||
ret <- .Call("XGBoosterPredict_R", booster, dmat, as.integer(outputmargin), PACKAGE="xgboost")
|
||||
return(ret)
|
||||
}
|
||||
# dump model
|
||||
xgb.dump <- function(booster, fname, fmap = "") {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
stop("xgb.dump: first argument must be type xgb.Booster")
|
||||
}
|
||||
if (typeof(fname) != "character"){
|
||||
stop("xgb.dump: second argument must be type character")
|
||||
}
|
||||
.Call("XGBoosterDumpModel_R", booster, fname, fmap, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
|
||||
##--------------------------------------
|
||||
# the following are low level iteratively function, not needed
|
||||
# if you do not want to use them
|
||||
#---------------------------------------
|
||||
|
||||
# iteratively update booster with dtrain
|
||||
xgb.iter.update <- function(booster, dtrain, iter) {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
@ -183,6 +87,7 @@ xgb.iter.update <- function(booster, dtrain, iter) {
|
||||
.Call("XGBoosterUpdateOneIter_R", booster, as.integer(iter), dtrain, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
|
||||
# iteratively update booster with customized statistics
|
||||
xgb.iter.boost <- function(booster, dtrain, gpair) {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
@ -194,6 +99,7 @@ xgb.iter.boost <- function(booster, dtrain, gpair) {
|
||||
.Call("XGBoosterBoostOneIter_R", booster, dtrain, gpair$grad, gpair$hess, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
|
||||
# iteratively evaluate one iteration
|
||||
xgb.iter.eval <- function(booster, watchlist, iter) {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
22
R-package/R/xgb.DMatrix.R
Normal file
22
R-package/R/xgb.DMatrix.R
Normal file
@ -0,0 +1,22 @@
|
||||
# constructing DMatrix
|
||||
xgb.DMatrix <- function(data, missing=0.0, ...) {
|
||||
if (typeof(data) == "character") {
|
||||
handle <- .Call("XGDMatrixCreateFromFile_R", data, as.integer(FALSE), PACKAGE="xgboost")
|
||||
} else if(is.matrix(data)) {
|
||||
handle <- .Call("XGDMatrixCreateFromMat_R", data, missing, PACKAGE="xgboost")
|
||||
} else if(class(data) == "dgCMatrix") {
|
||||
handle <- .Call("XGDMatrixCreateFromCSC_R", data@p, data@i, data@x, PACKAGE="xgboost")
|
||||
} else {
|
||||
stop(paste("xgb.DMatrix: does not support to construct from ", typeof(data)))
|
||||
}
|
||||
dmat <- structure(handle, class="xgb.DMatrix")
|
||||
|
||||
info = list(...)
|
||||
if (length(info)==0)
|
||||
return(dmat)
|
||||
for (i in 1:length(info)) {
|
||||
p = info[i]
|
||||
xgb.setinfo(dmat, names(p), p[[1]])
|
||||
}
|
||||
return(dmat)
|
||||
}
|
||||
11
R-package/R/xgb.dump.R
Normal file
11
R-package/R/xgb.dump.R
Normal file
@ -0,0 +1,11 @@
|
||||
# dump model
|
||||
xgb.dump <- function(booster, fname, fmap = "") {
|
||||
if (class(booster) != "xgb.Booster") {
|
||||
stop("xgb.dump: first argument must be type xgb.Booster")
|
||||
}
|
||||
if (typeof(fname) != "character"){
|
||||
stop("xgb.dump: second argument must be type character")
|
||||
}
|
||||
.Call("XGBoosterDumpModel_R", booster, fname, fmap, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
16
R-package/R/xgb.getinfo.R
Normal file
16
R-package/R/xgb.getinfo.R
Normal file
@ -0,0 +1,16 @@
|
||||
# get information from dmatrix
|
||||
xgb.getinfo <- function(dmat, name) {
|
||||
if (typeof(name) != "character") {
|
||||
stop("xgb.getinfo: name must be character")
|
||||
}
|
||||
if (class(dmat) != "xgb.DMatrix") {
|
||||
stop("xgb.setinfo: first argument dtrain must be xgb.DMatrix");
|
||||
}
|
||||
if (name != "label" &&
|
||||
name != "weight" &&
|
||||
name != "base_margin" ) {
|
||||
stop(paste("xgb.getinfo: unknown info name", name))
|
||||
}
|
||||
ret <- .Call("XGDMatrixGetInfo_R", dmat, name, PACKAGE="xgboost")
|
||||
return(ret)
|
||||
}
|
||||
5
R-package/R/xgb.load.R
Normal file
5
R-package/R/xgb.load.R
Normal file
@ -0,0 +1,5 @@
|
||||
xgb.load <- function(modelfile) {
|
||||
if (is.null(modelfile))
|
||||
stop('xgb.load: modelfile cannot be NULL')
|
||||
xgb.Booster(modelfile=modelfile)
|
||||
}
|
||||
16
R-package/R/xgb.save.R
Normal file
16
R-package/R/xgb.save.R
Normal file
@ -0,0 +1,16 @@
|
||||
# save model or DMatrix to file
|
||||
xgb.save <- function(handle, fname) {
|
||||
if (typeof(fname) != "character") {
|
||||
stop("xgb.save: fname must be character")
|
||||
}
|
||||
if (class(handle) == "xgb.Booster") {
|
||||
.Call("XGBoosterSaveModel_R", handle, fname, PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
if (class(handle) == "xgb.DMatrix") {
|
||||
.Call("XGDMatrixSaveBinary_R", handle, fname, as.integer(FALSE), PACKAGE="xgboost")
|
||||
return(TRUE)
|
||||
}
|
||||
stop("xgb.save: the input must be either xgb.DMatrix or xgb.Booster")
|
||||
return(FALSE)
|
||||
}
|
||||
38
R-package/R/xgb.train.R
Normal file
38
R-package/R/xgb.train.R
Normal file
@ -0,0 +1,38 @@
|
||||
# train a model using given parameters
|
||||
xgb.train <- function(params, dtrain, nrounds=10, watchlist=list(), obj=NULL, feval=NULL) {
|
||||
if (typeof(params) != "list") {
|
||||
stop("xgb.train: first argument params must be list");
|
||||
}
|
||||
if (class(dtrain) != "xgb.DMatrix") {
|
||||
stop("xgb.train: second argument dtrain must be xgb.DMatrix");
|
||||
}
|
||||
bst <- xgb.Booster(params, append(watchlist,dtrain))
|
||||
for (i in 1:nrounds) {
|
||||
if (is.null(obj)) {
|
||||
succ <- xgb.iter.update(bst, dtrain, i-1)
|
||||
} else {
|
||||
pred <- xgb.predict(bst, dtrain)
|
||||
gpair <- obj(pred, dtrain)
|
||||
succ <- xgb.iter.boost(bst, dtrain, gpair)
|
||||
}
|
||||
if (length(watchlist) != 0) {
|
||||
if (is.null(feval)) {
|
||||
msg <- xgb.iter.eval(bst, watchlist, i-1)
|
||||
cat(msg); cat("\n")
|
||||
} else {
|
||||
cat("["); cat(i); cat("]");
|
||||
for (j in 1:length(watchlist)) {
|
||||
w <- watchlist[j]
|
||||
if (length(names(w)) == 0) {
|
||||
stop("xgb.eval: name tag must be presented for every elements in watchlist")
|
||||
}
|
||||
ret <- feval(xgb.predict(bst, w[[1]]), w[[1]])
|
||||
cat("\t"); cat(names(w)); cat("-"); cat(ret$metric);
|
||||
cat(":"); cat(ret$value)
|
||||
}
|
||||
cat("\n")
|
||||
}
|
||||
}
|
||||
}
|
||||
return(bst)
|
||||
}
|
||||
@ -1,23 +1,48 @@
|
||||
# Main function for xgboost-package
|
||||
|
||||
xgboost = function(x=NULL,y=NULL,file=NULL,nrounds=10,params,watchlist=list(),
|
||||
obj=NULL, feval=NULL, margin=NULL)
|
||||
xgboost = function(x=NULL,y=NULL,DMatrix=NULL, file=NULL, validation=NULL,
|
||||
nrounds=10, obj=NULL, feval=NULL, margin=NULL, verbose = T, ...)
|
||||
{
|
||||
if (is.null(x) && is.null(y))
|
||||
{
|
||||
if (is.null(file))
|
||||
stop('xgboost need input data, either R objects or local files.')
|
||||
dtrain = xgb.DMatrix(file)
|
||||
}
|
||||
if (!is.null(DMatrix))
|
||||
dtrain = DMatrix
|
||||
else
|
||||
dtrain = xgb.DMatrix(x, info=list(label=y))
|
||||
if (!is.null(margin))
|
||||
{
|
||||
succ <- xgb.setinfo(dtrain, "base_margin", margin)
|
||||
if (!succ)
|
||||
warning('Attemp to use margin failed.')
|
||||
if (is.null(x) && is.null(y))
|
||||
{
|
||||
if (is.null(file))
|
||||
stop('xgboost need input data, either R objects, local files or DMatrix object.')
|
||||
dtrain = xgb.DMatrix(file)
|
||||
}
|
||||
else
|
||||
dtrain = xgb.DMatrix(x, label=y)
|
||||
if (!is.null(margin))
|
||||
{
|
||||
succ <- xgb.setinfo(dtrain, "base_margin", margin)
|
||||
if (!succ)
|
||||
warning('Attemp to use margin failed.')
|
||||
}
|
||||
}
|
||||
|
||||
params = list(...)
|
||||
|
||||
watchlist=list()
|
||||
if (verbose)
|
||||
{
|
||||
if (!is.null(validation))
|
||||
{
|
||||
if (class(validation)!='xgb.DMatrix')
|
||||
dtest = xgb.DMatrix(validation)
|
||||
else
|
||||
dtest = validation
|
||||
watchlist = list(eval=dtest,train=dtrain)
|
||||
}
|
||||
|
||||
else
|
||||
watchlist = list(train=dtrain)
|
||||
}
|
||||
|
||||
bst <- xgb.train(params, dtrain, nrounds, watchlist, obj, feval)
|
||||
|
||||
return(bst)
|
||||
}
|
||||
|
||||
|
||||
133
R-package/inst/examples/demo-new.R
Normal file
133
R-package/inst/examples/demo-new.R
Normal file
@ -0,0 +1,133 @@
|
||||
require(xgboost)
|
||||
require(methods)
|
||||
|
||||
# helper function to read libsvm format
|
||||
# this is very badly written, load in dense, and convert to sparse
|
||||
# use this only for demo purpose
|
||||
# adopted from https://github.com/zygmuntz/r-libsvm-format-read-write/blob/master/f_read.libsvm.r
|
||||
read.libsvm = function(fname, maxcol) {
|
||||
content = readLines(fname)
|
||||
nline = length(content)
|
||||
label = numeric(nline)
|
||||
mat = matrix(0, nline, maxcol+1)
|
||||
for (i in 1:nline) {
|
||||
arr = as.vector(strsplit(content[i], " ")[[1]])
|
||||
label[i] = as.numeric(arr[[1]])
|
||||
for (j in 2:length(arr)) {
|
||||
kv = strsplit(arr[j], ":")[[1]]
|
||||
# to avoid 0 index
|
||||
findex = as.integer(kv[1]) + 1
|
||||
fvalue = as.numeric(kv[2])
|
||||
mat[i,findex] = fvalue
|
||||
}
|
||||
}
|
||||
mat = as(mat, "sparseMatrix")
|
||||
return(list(label=label, data=mat))
|
||||
}
|
||||
|
||||
############################
|
||||
# Test xgb.DMatrix with local file, sparse matrix and dense matrix in R.
|
||||
############################
|
||||
|
||||
# Directly read in local file
|
||||
dtrain = xgb.DMatrix('agaricus.txt.train')
|
||||
class(dtrain)
|
||||
|
||||
# read file in R
|
||||
csc = read.libsvm("agaricus.txt.train", 126)
|
||||
y = csc$label
|
||||
x = csc$data
|
||||
|
||||
# x as Sparse Matrix
|
||||
class(x)
|
||||
dtrain = xgb.DMatrix(x, label=y)
|
||||
|
||||
# x as dense matrix
|
||||
dense.x = as.matrix(x)
|
||||
dtrain = xgb.DMatrix(dense.x, label=y)
|
||||
|
||||
############################
|
||||
# Test xgboost with local file, sparse matrix and dense matrix in R.
|
||||
############################
|
||||
|
||||
# Test with DMatrix object
|
||||
bst = xgboost(DMatrix=dtrain, max_depth=2, eta=1, silent=1, objective='binary:logistic')
|
||||
|
||||
# Test with local file
|
||||
bst = xgboost(file='agaricus.txt.train', max_depth=2, eta=1, silent=1, objective='binary:logistic')
|
||||
|
||||
# Test with Sparse Matrix
|
||||
bst = xgboost(x = x, y = y, max_depth=2, eta=1, silent=1, objective='binary:logistic')
|
||||
|
||||
# Test with dense Matrix
|
||||
bst = xgboost(x = dense.x, y = y, max_depth=2, eta=1, silent=1, objective='binary:logistic')
|
||||
|
||||
# Test with validation set
|
||||
bst = xgboost(file='agaricus.txt.train', validation='agaricus.txt.test',
|
||||
max_depth=2, eta=1, silent=1, objective='binary:logistic')
|
||||
|
||||
############################
|
||||
# Test predict
|
||||
############################
|
||||
|
||||
# Prediction with DMatrix object
|
||||
dtest = xgb.DMatrix('agaricus.txt.test')
|
||||
pred = predict(bst, dtest)
|
||||
|
||||
# Prediction with local test file
|
||||
pred = predict(bst, 'agaricus.txt.test')
|
||||
|
||||
# Prediction with Sparse Matrix
|
||||
csc = read.libsvm("agaricus.txt.test", 126)
|
||||
test.y = csc$label
|
||||
test.x = csc$data
|
||||
pred = predict(bst, test.x)
|
||||
|
||||
# Extrac label with xgb.getinfo
|
||||
labels = xgb.getinfo(dtest, "label")
|
||||
err = as.numeric(sum(as.integer(pred > 0.5) != labels)) / length(labels)
|
||||
print(paste("error=",err))
|
||||
|
||||
############################
|
||||
# Save and load model to hard disk
|
||||
############################
|
||||
|
||||
# save model to binary local file
|
||||
xgb.save(bst, 'model.save')
|
||||
|
||||
# load binary model to R
|
||||
bst = xgb.load('model.save')
|
||||
pred = predict(bst, test.x)
|
||||
|
||||
# save model to text file
|
||||
xgb.dump(bst, 'model.dump')
|
||||
|
||||
############################
|
||||
# Customized objective and evaluation function
|
||||
############################
|
||||
|
||||
# user define objective function, given prediction, return gradient and second order gradient
|
||||
# this is loglikelihood loss
|
||||
logregobj = function(preds, dtrain) {
|
||||
labels = xgb.getinfo(dtrain, "label")
|
||||
preds = 1.0 / (1.0 + exp(-preds))
|
||||
grad = preds - labels
|
||||
hess = preds * (1.0-preds)
|
||||
return(list(grad=grad, hess=hess))
|
||||
}
|
||||
# user defined evaluation function, return a list(metric="metric-name", value="metric-value")
|
||||
# NOTE: when you do customized loss function, the default prediction value is margin
|
||||
# this may make buildin evalution metric not function properly
|
||||
# for example, we are doing logistic loss, the prediction is score before logistic transformation
|
||||
# the buildin evaluation error assumes input is after logistic transformation
|
||||
# Take this in mind when you use the customization, and maybe you need write customized evaluation function
|
||||
evalerror = function(preds, dtrain) {
|
||||
labels = xgb.getinfo(dtrain, "label")
|
||||
err = as.numeric(sum(labels != (preds > 0.0))) / length(labels)
|
||||
return(list(metric="error", value=err))
|
||||
}
|
||||
|
||||
bst = xgboost(x = x, y = y, max_depth=2, eta=1, silent=1, objective='binary:logistic',
|
||||
obj=logregobj, feval=evalerror)
|
||||
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
require(xgboost)
|
||||
require(methods)
|
||||
|
||||
# helper function to read libsvm format
|
||||
# this is very badly written, load in dense, and convert to sparse
|
||||
|
||||
72
R-package/inst/examples/model.dump
Normal file
72
R-package/inst/examples/model.dump
Normal file
@ -0,0 +1,72 @@
|
||||
booster[0]:
|
||||
0:[f28<1.00001] yes=1,no=2,missing=2
|
||||
1:[f108<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=1.85965
|
||||
4:leaf=-1.94071
|
||||
2:[f55<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=-1.70044
|
||||
6:leaf=1.71218
|
||||
booster[1]:
|
||||
0:[f59<1.00001] yes=1,no=2,missing=2
|
||||
1:leaf=-6.23624
|
||||
2:[f28<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=-0.96853
|
||||
4:leaf=0.784718
|
||||
booster[2]:
|
||||
0:[f101<1.00001] yes=1,no=2,missing=2
|
||||
1:[f110<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=-9.42142
|
||||
4:leaf=-0.791407
|
||||
2:[f66<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=5.77229
|
||||
6:leaf=0.658725
|
||||
booster[3]:
|
||||
0:[f26<1.00001] yes=1,no=2,missing=2
|
||||
1:leaf=1.07748
|
||||
2:[f38<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=-0.877906
|
||||
4:leaf=0.614153
|
||||
booster[4]:
|
||||
0:[f108<1.00001] yes=1,no=2,missing=2
|
||||
1:leaf=2.92191
|
||||
2:[f35<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=0.152607
|
||||
4:leaf=-1.26934
|
||||
booster[5]:
|
||||
0:[f22<1.00001] yes=1,no=2,missing=2
|
||||
1:[f35<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=-1.02315
|
||||
4:leaf=-3.02414
|
||||
2:[f23<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=-1.53846
|
||||
6:leaf=0.431742
|
||||
booster[6]:
|
||||
0:[f28<1.00001] yes=1,no=2,missing=2
|
||||
1:[f108<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=0.836115
|
||||
4:leaf=-0.912605
|
||||
2:[f23<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=-1.1971
|
||||
6:leaf=0.777142
|
||||
booster[7]:
|
||||
0:[f38<1.00001] yes=1,no=2,missing=2
|
||||
1:[f26<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=0.890623
|
||||
4:leaf=-0.908312
|
||||
2:[f111<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=1.43619
|
||||
6:leaf=-0.0180106
|
||||
booster[8]:
|
||||
0:[f22<1.00001] yes=1,no=2,missing=2
|
||||
1:leaf=-1.01502
|
||||
2:[f101<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=0.568838
|
||||
4:leaf=-0.515293
|
||||
booster[9]:
|
||||
0:[f114<1.00001] yes=1,no=2,missing=2
|
||||
1:[f60<1.00001] yes=3,no=4,missing=4
|
||||
3:leaf=-0.609475
|
||||
4:leaf=3.63443
|
||||
2:[f28<1.00001] yes=5,no=6,missing=6
|
||||
5:leaf=-0.734556
|
||||
6:leaf=0.217203
|
||||
28
R-package/src-i386/Makevars
Normal file
28
R-package/src-i386/Makevars
Normal file
@ -0,0 +1,28 @@
|
||||
# _*_ mode: Makefile; _*_
|
||||
export CC = gcc
|
||||
export CXX = g++
|
||||
|
||||
# expose these flags to R CMD SHLIB
|
||||
PKG_CPPFLAGS = -O3 -Wno-unknown-pragmas -DXGBOOST_CUSTOMIZE_ERROR_ -fPIC $(SHLIB_OPENMP_CFLAGS)
|
||||
PKG_LIBS = $(SHLIB_OPENMP_CFLAGS)
|
||||
|
||||
ifeq ($(no_omp),1)
|
||||
PKG_CPPFLAGS += -DDISABLE_OPENMP
|
||||
endif
|
||||
|
||||
CXXOBJ= xgboost_wrapper.o xgboost_io.o
|
||||
OBJECTS= xgboost_R.o $(CXXOBJ)
|
||||
|
||||
.PHONY: all clean
|
||||
all: $(SHLIB)
|
||||
$(SHLIB): $(OBJECTS)
|
||||
|
||||
xgboost_wrapper.o: ../../wrapper/xgboost_wrapper.cpp
|
||||
xgboost_io.o: ../../src/io/io.cpp
|
||||
|
||||
$(CXXOBJ) :
|
||||
$(CXX) -c $(PKG_CPPFLAGS) -o $@ $(firstword $(filter %.cpp %.c, $^) )
|
||||
|
||||
clean:
|
||||
rm -rf *.so *.o *~ *.dll
|
||||
|
||||
32
R-package/src-i386/Makevars.win
Normal file
32
R-package/src-i386/Makevars.win
Normal file
@ -0,0 +1,32 @@
|
||||
# _*_ mode: Makefile; _*_
|
||||
export CC = gcc
|
||||
export CXX = g++
|
||||
|
||||
# expose these flags to R CMD SHLIB
|
||||
PKG_CPPFLAGS = -O3 -Wno-unknown-pragmas -DXGBOOST_CUSTOMIZE_ERROR_ -fopenmp -fPIC $(SHLIB_OPENMP_CFLAGS)
|
||||
PKG_LIBS = $(SHLIB_OPENMP_CFLAGS)
|
||||
|
||||
# add flag to build native code even in cross compiler
|
||||
ifeq "$(WIN)" "64"
|
||||
PKG_CPPFLAGS += -m64
|
||||
endif
|
||||
|
||||
ifeq ($(no_omp),1)
|
||||
PKG_CPPFLAGS += -DDISABLE_OPENMP
|
||||
endif
|
||||
|
||||
CXXOBJ= xgboost_wrapper.o xgboost_io.o
|
||||
OBJECTS= xgboost_R.o $(CXXOBJ)
|
||||
|
||||
.PHONY: all clean
|
||||
all: $(SHLIB)
|
||||
$(SHLIB): $(OBJECTS)
|
||||
|
||||
xgboost_wrapper.o: ../../wrapper/xgboost_wrapper.cpp
|
||||
xgboost_io.o: ../../src/io/io.cpp
|
||||
|
||||
$(CXXOBJ) :
|
||||
$(CXX) -c $(PKG_CPPFLAGS) -o $@ $(firstword $(filter %.cpp %.c, $^) )
|
||||
|
||||
clean:
|
||||
rm -rf *.so *.o *~ *.dll
|
||||
221
R-package/src-i386/xgboost_R.cpp
Normal file
221
R-package/src-i386/xgboost_R.cpp
Normal file
@ -0,0 +1,221 @@
|
||||
#include <vector>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
#include <cstring>
|
||||
#include "xgboost_R.h"
|
||||
#include "../../wrapper/xgboost_wrapper.h"
|
||||
#include "../../src/utils/utils.h"
|
||||
#include "../../src/utils/omp.h"
|
||||
#include "../../src/utils/matrix_csr.h"
|
||||
|
||||
using namespace xgboost;
|
||||
// implements error handling
|
||||
namespace xgboost {
|
||||
namespace utils {
|
||||
void HandleAssertError(const char *msg) {
|
||||
error("%s", msg);
|
||||
}
|
||||
void HandleCheckError(const char *msg) {
|
||||
error("%s", msg);
|
||||
}
|
||||
} // namespace utils
|
||||
} // namespace xgboost
|
||||
|
||||
extern "C" {
|
||||
void _DMatrixFinalizer(SEXP ext) {
|
||||
if (R_ExternalPtrAddr(ext) == NULL) return;
|
||||
XGDMatrixFree(R_ExternalPtrAddr(ext));
|
||||
R_ClearExternalPtr(ext);
|
||||
}
|
||||
SEXP XGDMatrixCreateFromFile_R(SEXP fname, SEXP silent) {
|
||||
void *handle = XGDMatrixCreateFromFile(CHAR(asChar(fname)), asInteger(silent));
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
SEXP XGDMatrixCreateFromMat_R(SEXP mat,
|
||||
SEXP missing) {
|
||||
SEXP dim = getAttrib(mat, R_DimSymbol);
|
||||
int nrow = INTEGER(dim)[0];
|
||||
int ncol = INTEGER(dim)[1];
|
||||
double *din = REAL(mat);
|
||||
std::vector<float> data(nrow * ncol);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < nrow; ++i) {
|
||||
for (int j = 0; j < ncol; ++j) {
|
||||
data[i * ncol +j] = din[i + nrow * j];
|
||||
}
|
||||
}
|
||||
void *handle = XGDMatrixCreateFromMat(&data[0], nrow, ncol, asReal(missing));
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
SEXP XGDMatrixCreateFromCSC_R(SEXP indptr,
|
||||
SEXP indices,
|
||||
SEXP data) {
|
||||
const int *col_ptr = INTEGER(indptr);
|
||||
const int *row_index = INTEGER(indices);
|
||||
const double *col_data = REAL(data);
|
||||
int ncol = length(indptr) - 1;
|
||||
int ndata = length(data);
|
||||
// transform into CSR format
|
||||
std::vector<bst_ulong> row_ptr;
|
||||
std::vector< std::pair<unsigned, float> > csr_data;
|
||||
utils::SparseCSRMBuilder<std::pair<unsigned,float>, false, bst_ulong> builder(row_ptr, csr_data);
|
||||
builder.InitBudget();
|
||||
for (int i = 0; i < ncol; ++i) {
|
||||
for (int j = col_ptr[i]; j < col_ptr[i+1]; ++j) {
|
||||
builder.AddBudget(row_index[j]);
|
||||
}
|
||||
}
|
||||
builder.InitStorage();
|
||||
for (int i = 0; i < ncol; ++i) {
|
||||
for (int j = col_ptr[i]; j < col_ptr[i+1]; ++j) {
|
||||
builder.PushElem(row_index[j], std::make_pair(i, col_data[j]));
|
||||
}
|
||||
}
|
||||
utils::Assert(csr_data.size() == static_cast<size_t>(ndata), "BUG CreateFromCSC");
|
||||
std::vector<float> row_data(ndata);
|
||||
std::vector<unsigned> col_index(ndata);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < ndata; ++i) {
|
||||
col_index[i] = csr_data[i].first;
|
||||
row_data[i] = csr_data[i].second;
|
||||
}
|
||||
void *handle = XGDMatrixCreateFromCSR(&row_ptr[0], &col_index[0], &row_data[0], row_ptr.size(), ndata );
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGDMatrixSaveBinary_R(SEXP handle, SEXP fname, SEXP silent) {
|
||||
XGDMatrixSaveBinary(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(fname)), asInteger(silent));
|
||||
}
|
||||
void XGDMatrixSetInfo_R(SEXP handle, SEXP field, SEXP array) {
|
||||
int len = length(array);
|
||||
const char *name = CHAR(asChar(field));
|
||||
if (!strcmp("group", name)) {
|
||||
std::vector<unsigned> vec(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec[i] = static_cast<unsigned>(INTEGER(array)[i]);
|
||||
}
|
||||
XGDMatrixSetGroup(R_ExternalPtrAddr(handle), &vec[0], len);
|
||||
return;
|
||||
}
|
||||
{
|
||||
std::vector<float> vec(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec[i] = REAL(array)[i];
|
||||
}
|
||||
XGDMatrixSetFloatInfo(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(field)),
|
||||
&vec[0], len);
|
||||
}
|
||||
}
|
||||
SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field) {
|
||||
bst_ulong olen;
|
||||
const float *res = XGDMatrixGetFloatInfo(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(field)), &olen);
|
||||
SEXP ret = PROTECT(allocVector(REALSXP, olen));
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
REAL(ret)[i] = res[i];
|
||||
}
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
// functions related to booster
|
||||
void _BoosterFinalizer(SEXP ext) {
|
||||
if (R_ExternalPtrAddr(ext) == NULL) return;
|
||||
XGBoosterFree(R_ExternalPtrAddr(ext));
|
||||
R_ClearExternalPtr(ext);
|
||||
}
|
||||
SEXP XGBoosterCreate_R(SEXP dmats) {
|
||||
int len = length(dmats);
|
||||
std::vector<void*> dvec;
|
||||
for (int i = 0; i < len; ++i){
|
||||
dvec.push_back(R_ExternalPtrAddr(VECTOR_ELT(dmats, i)));
|
||||
}
|
||||
void *handle = XGBoosterCreate(&dvec[0], dvec.size());
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _BoosterFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGBoosterSetParam_R(SEXP handle, SEXP name, SEXP val) {
|
||||
XGBoosterSetParam(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(name)),
|
||||
CHAR(asChar(val)));
|
||||
}
|
||||
void XGBoosterUpdateOneIter_R(SEXP handle, SEXP iter, SEXP dtrain) {
|
||||
XGBoosterUpdateOneIter(R_ExternalPtrAddr(handle),
|
||||
asInteger(iter),
|
||||
R_ExternalPtrAddr(dtrain));
|
||||
}
|
||||
void XGBoosterBoostOneIter_R(SEXP handle, SEXP dtrain, SEXP grad, SEXP hess) {
|
||||
utils::Check(length(grad) == length(hess), "gradient and hess must have same length");
|
||||
int len = length(grad);
|
||||
std::vector<float> tgrad(len), thess(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int j = 0; j < len; ++j) {
|
||||
tgrad[j] = REAL(grad)[j];
|
||||
thess[j] = REAL(hess)[j];
|
||||
}
|
||||
XGBoosterBoostOneIter(R_ExternalPtrAddr(handle),
|
||||
R_ExternalPtrAddr(dtrain),
|
||||
&tgrad[0], &thess[0], len);
|
||||
}
|
||||
SEXP XGBoosterEvalOneIter_R(SEXP handle, SEXP iter, SEXP dmats, SEXP evnames) {
|
||||
utils::Check(length(dmats) == length(evnames), "dmats and evnams must have same length");
|
||||
int len = length(dmats);
|
||||
std::vector<void*> vec_dmats;
|
||||
std::vector<std::string> vec_names;
|
||||
std::vector<const char*> vec_sptr;
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec_dmats.push_back(R_ExternalPtrAddr(VECTOR_ELT(dmats, i)));
|
||||
vec_names.push_back(std::string(CHAR(asChar(VECTOR_ELT(evnames, i)))));
|
||||
}
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec_sptr.push_back(vec_names[i].c_str());
|
||||
}
|
||||
return mkString(XGBoosterEvalOneIter(R_ExternalPtrAddr(handle),
|
||||
asInteger(iter),
|
||||
&vec_dmats[0], &vec_sptr[0], len));
|
||||
}
|
||||
SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin) {
|
||||
bst_ulong olen;
|
||||
const float *res = XGBoosterPredict(R_ExternalPtrAddr(handle),
|
||||
R_ExternalPtrAddr(dmat),
|
||||
asInteger(output_margin),
|
||||
&olen);
|
||||
SEXP ret = PROTECT(allocVector(REALSXP, olen));
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
REAL(ret)[i] = res[i];
|
||||
}
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGBoosterLoadModel_R(SEXP handle, SEXP fname) {
|
||||
XGBoosterLoadModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
|
||||
}
|
||||
void XGBoosterSaveModel_R(SEXP handle, SEXP fname) {
|
||||
XGBoosterSaveModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
|
||||
}
|
||||
void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap) {
|
||||
bst_ulong olen;
|
||||
const char **res = XGBoosterDumpModel(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(fmap)),
|
||||
&olen);
|
||||
FILE *fo = utils::FopenCheck(CHAR(asChar(fname)), "w");
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
fprintf(fo, "booster[%u]:\n", static_cast<unsigned>(i));
|
||||
fprintf(fo, "%s", res[i]);
|
||||
}
|
||||
fclose(fo);
|
||||
}
|
||||
}
|
||||
124
R-package/src-i386/xgboost_R.h
Normal file
124
R-package/src-i386/xgboost_R.h
Normal file
@ -0,0 +1,124 @@
|
||||
#ifndef XGBOOST_WRAPPER_R_H_
|
||||
#define XGBOOST_WRAPPER_R_H_
|
||||
/*!
|
||||
* \file xgboost_wrapper_R.h
|
||||
* \author Tianqi Chen
|
||||
* \brief R wrapper of xgboost
|
||||
*/
|
||||
extern "C" {
|
||||
#include <Rinternals.h>
|
||||
}
|
||||
|
||||
extern "C" {
|
||||
/*!
|
||||
* \brief load a data matrix
|
||||
* \param fname name of the content
|
||||
* \param silent whether print messages
|
||||
* \return a loaded data matrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromFile_R(SEXP fname, SEXP silent);
|
||||
/*!
|
||||
* \brief create matrix content from dense matrix
|
||||
* This assumes the matrix is stored in column major format
|
||||
* \param data R Matrix object
|
||||
* \param missing which value to represent missing value
|
||||
* \return created dmatrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromMat_R(SEXP mat,
|
||||
SEXP missing);
|
||||
/*!
|
||||
* \brief create a matrix content from CSC format
|
||||
* \param indptr pointer to column headers
|
||||
* \param indices row indices
|
||||
* \param data content of the data
|
||||
* \return created dmatrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromCSC_R(SEXP indptr,
|
||||
SEXP indices,
|
||||
SEXP data);
|
||||
/*!
|
||||
* \brief load a data matrix into binary file
|
||||
* \param handle a instance of data matrix
|
||||
* \param fname file name
|
||||
* \param silent print statistics when saving
|
||||
*/
|
||||
void XGDMatrixSaveBinary_R(SEXP handle, SEXP fname, SEXP silent);
|
||||
/*!
|
||||
* \brief set information to dmatrix
|
||||
* \param handle a instance of data matrix
|
||||
* \param field field name, can be label, weight
|
||||
* \param array pointer to float vector
|
||||
*/
|
||||
void XGDMatrixSetInfo_R(SEXP handle, SEXP field, SEXP array);
|
||||
/*!
|
||||
* \brief get info vector from matrix
|
||||
* \param handle a instance of data matrix
|
||||
* \param field field name
|
||||
* \return info vector
|
||||
*/
|
||||
SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field);
|
||||
/*!
|
||||
* \brief create xgboost learner
|
||||
* \param dmats a list of dmatrix handles that will be cached
|
||||
*/
|
||||
SEXP XGBoosterCreate_R(SEXP dmats);
|
||||
/*!
|
||||
* \brief set parameters
|
||||
* \param handle handle
|
||||
* \param name parameter name
|
||||
* \param val value of parameter
|
||||
*/
|
||||
void XGBoosterSetParam_R(SEXP handle, SEXP name, SEXP val);
|
||||
/*!
|
||||
* \brief update the model in one round using dtrain
|
||||
* \param handle handle
|
||||
* \param iter current iteration rounds
|
||||
* \param dtrain training data
|
||||
*/
|
||||
void XGBoosterUpdateOneIter_R(SEXP ext, SEXP iter, SEXP dtrain);
|
||||
/*!
|
||||
* \brief update the model, by directly specify gradient and second order gradient,
|
||||
* this can be used to replace UpdateOneIter, to support customized loss function
|
||||
* \param handle handle
|
||||
* \param dtrain training data
|
||||
* \param grad gradient statistics
|
||||
* \param hess second order gradient statistics
|
||||
*/
|
||||
void XGBoosterBoostOneIter_R(SEXP handle, SEXP dtrain, SEXP grad, SEXP hess);
|
||||
/*!
|
||||
* \brief get evaluation statistics for xgboost
|
||||
* \param handle handle
|
||||
* \param iter current iteration rounds
|
||||
* \param dmats list of handles to dmatrices
|
||||
* \param evname name of evaluation
|
||||
* \return the string containing evaluation stati
|
||||
*/
|
||||
SEXP XGBoosterEvalOneIter_R(SEXP handle, SEXP iter, SEXP dmats, SEXP evnames);
|
||||
/*!
|
||||
* \brief make prediction based on dmat
|
||||
* \param handle handle
|
||||
* \param dmat data matrix
|
||||
* \param output_margin whether only output raw margin value
|
||||
*/
|
||||
SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin);
|
||||
/*!
|
||||
* \brief load model from existing file
|
||||
* \param handle handle
|
||||
* \param fname file name
|
||||
*/
|
||||
void XGBoosterLoadModel_R(SEXP handle, SEXP fname);
|
||||
/*!
|
||||
* \brief save model into existing file
|
||||
* \param handle handle
|
||||
* \param fname file name
|
||||
*/
|
||||
void XGBoosterSaveModel_R(SEXP handle, SEXP fname);
|
||||
/*!
|
||||
* \brief dump model into text file
|
||||
* \param handle handle
|
||||
* \param fname file name of model that can be dumped into
|
||||
* \param fmap name to fmap can be empty string
|
||||
*/
|
||||
void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap);
|
||||
};
|
||||
#endif // XGBOOST_WRAPPER_R_H_
|
||||
28
R-package/src-x64/Makevars
Normal file
28
R-package/src-x64/Makevars
Normal file
@ -0,0 +1,28 @@
|
||||
# _*_ mode: Makefile; _*_
|
||||
export CC = gcc
|
||||
export CXX = g++
|
||||
|
||||
# expose these flags to R CMD SHLIB
|
||||
PKG_CPPFLAGS = -O3 -Wno-unknown-pragmas -DXGBOOST_CUSTOMIZE_ERROR_ -fPIC $(SHLIB_OPENMP_CFLAGS)
|
||||
PKG_LIBS = $(SHLIB_OPENMP_CFLAGS)
|
||||
|
||||
ifeq ($(no_omp),1)
|
||||
PKG_CPPFLAGS += -DDISABLE_OPENMP
|
||||
endif
|
||||
|
||||
CXXOBJ= xgboost_wrapper.o xgboost_io.o
|
||||
OBJECTS= xgboost_R.o $(CXXOBJ)
|
||||
|
||||
.PHONY: all clean
|
||||
all: $(SHLIB)
|
||||
$(SHLIB): $(OBJECTS)
|
||||
|
||||
xgboost_wrapper.o: ../../wrapper/xgboost_wrapper.cpp
|
||||
xgboost_io.o: ../../src/io/io.cpp
|
||||
|
||||
$(CXXOBJ) :
|
||||
$(CXX) -c $(PKG_CPPFLAGS) -o $@ $(firstword $(filter %.cpp %.c, $^) )
|
||||
|
||||
clean:
|
||||
rm -rf *.so *.o *~ *.dll
|
||||
|
||||
32
R-package/src-x64/Makevars.win
Normal file
32
R-package/src-x64/Makevars.win
Normal file
@ -0,0 +1,32 @@
|
||||
# _*_ mode: Makefile; _*_
|
||||
export CC = gcc
|
||||
export CXX = g++
|
||||
|
||||
# expose these flags to R CMD SHLIB
|
||||
PKG_CPPFLAGS = -O3 -Wno-unknown-pragmas -DXGBOOST_CUSTOMIZE_ERROR_ -fopenmp -fPIC $(SHLIB_OPENMP_CFLAGS)
|
||||
PKG_LIBS = $(SHLIB_OPENMP_CFLAGS)
|
||||
|
||||
# add flag to build native code even in cross compiler
|
||||
ifeq "$(WIN)" "64"
|
||||
PKG_CPPFLAGS += -m64
|
||||
endif
|
||||
|
||||
ifeq ($(no_omp),1)
|
||||
PKG_CPPFLAGS += -DDISABLE_OPENMP
|
||||
endif
|
||||
|
||||
CXXOBJ= xgboost_wrapper.o xgboost_io.o
|
||||
OBJECTS= xgboost_R.o $(CXXOBJ)
|
||||
|
||||
.PHONY: all clean
|
||||
all: $(SHLIB)
|
||||
$(SHLIB): $(OBJECTS)
|
||||
|
||||
xgboost_wrapper.o: ../../wrapper/xgboost_wrapper.cpp
|
||||
xgboost_io.o: ../../src/io/io.cpp
|
||||
|
||||
$(CXXOBJ) :
|
||||
$(CXX) -c $(PKG_CPPFLAGS) -o $@ $(firstword $(filter %.cpp %.c, $^) )
|
||||
|
||||
clean:
|
||||
rm -rf *.so *.o *~ *.dll
|
||||
221
R-package/src-x64/xgboost_R.cpp
Normal file
221
R-package/src-x64/xgboost_R.cpp
Normal file
@ -0,0 +1,221 @@
|
||||
#include <vector>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
#include <cstring>
|
||||
#include "xgboost_R.h"
|
||||
#include "../../wrapper/xgboost_wrapper.h"
|
||||
#include "../../src/utils/utils.h"
|
||||
#include "../../src/utils/omp.h"
|
||||
#include "../../src/utils/matrix_csr.h"
|
||||
|
||||
using namespace xgboost;
|
||||
// implements error handling
|
||||
namespace xgboost {
|
||||
namespace utils {
|
||||
void HandleAssertError(const char *msg) {
|
||||
error("%s", msg);
|
||||
}
|
||||
void HandleCheckError(const char *msg) {
|
||||
error("%s", msg);
|
||||
}
|
||||
} // namespace utils
|
||||
} // namespace xgboost
|
||||
|
||||
extern "C" {
|
||||
void _DMatrixFinalizer(SEXP ext) {
|
||||
if (R_ExternalPtrAddr(ext) == NULL) return;
|
||||
XGDMatrixFree(R_ExternalPtrAddr(ext));
|
||||
R_ClearExternalPtr(ext);
|
||||
}
|
||||
SEXP XGDMatrixCreateFromFile_R(SEXP fname, SEXP silent) {
|
||||
void *handle = XGDMatrixCreateFromFile(CHAR(asChar(fname)), asInteger(silent));
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
SEXP XGDMatrixCreateFromMat_R(SEXP mat,
|
||||
SEXP missing) {
|
||||
SEXP dim = getAttrib(mat, R_DimSymbol);
|
||||
int nrow = INTEGER(dim)[0];
|
||||
int ncol = INTEGER(dim)[1];
|
||||
double *din = REAL(mat);
|
||||
std::vector<float> data(nrow * ncol);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < nrow; ++i) {
|
||||
for (int j = 0; j < ncol; ++j) {
|
||||
data[i * ncol +j] = din[i + nrow * j];
|
||||
}
|
||||
}
|
||||
void *handle = XGDMatrixCreateFromMat(&data[0], nrow, ncol, asReal(missing));
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
SEXP XGDMatrixCreateFromCSC_R(SEXP indptr,
|
||||
SEXP indices,
|
||||
SEXP data) {
|
||||
const int *col_ptr = INTEGER(indptr);
|
||||
const int *row_index = INTEGER(indices);
|
||||
const double *col_data = REAL(data);
|
||||
int ncol = length(indptr) - 1;
|
||||
int ndata = length(data);
|
||||
// transform into CSR format
|
||||
std::vector<bst_ulong> row_ptr;
|
||||
std::vector< std::pair<unsigned, float> > csr_data;
|
||||
utils::SparseCSRMBuilder<std::pair<unsigned,float>, false, bst_ulong> builder(row_ptr, csr_data);
|
||||
builder.InitBudget();
|
||||
for (int i = 0; i < ncol; ++i) {
|
||||
for (int j = col_ptr[i]; j < col_ptr[i+1]; ++j) {
|
||||
builder.AddBudget(row_index[j]);
|
||||
}
|
||||
}
|
||||
builder.InitStorage();
|
||||
for (int i = 0; i < ncol; ++i) {
|
||||
for (int j = col_ptr[i]; j < col_ptr[i+1]; ++j) {
|
||||
builder.PushElem(row_index[j], std::make_pair(i, col_data[j]));
|
||||
}
|
||||
}
|
||||
utils::Assert(csr_data.size() == static_cast<size_t>(ndata), "BUG CreateFromCSC");
|
||||
std::vector<float> row_data(ndata);
|
||||
std::vector<unsigned> col_index(ndata);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < ndata; ++i) {
|
||||
col_index[i] = csr_data[i].first;
|
||||
row_data[i] = csr_data[i].second;
|
||||
}
|
||||
void *handle = XGDMatrixCreateFromCSR(&row_ptr[0], &col_index[0], &row_data[0], row_ptr.size(), ndata );
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _DMatrixFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGDMatrixSaveBinary_R(SEXP handle, SEXP fname, SEXP silent) {
|
||||
XGDMatrixSaveBinary(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(fname)), asInteger(silent));
|
||||
}
|
||||
void XGDMatrixSetInfo_R(SEXP handle, SEXP field, SEXP array) {
|
||||
int len = length(array);
|
||||
const char *name = CHAR(asChar(field));
|
||||
if (!strcmp("group", name)) {
|
||||
std::vector<unsigned> vec(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec[i] = static_cast<unsigned>(INTEGER(array)[i]);
|
||||
}
|
||||
XGDMatrixSetGroup(R_ExternalPtrAddr(handle), &vec[0], len);
|
||||
return;
|
||||
}
|
||||
{
|
||||
std::vector<float> vec(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec[i] = REAL(array)[i];
|
||||
}
|
||||
XGDMatrixSetFloatInfo(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(field)),
|
||||
&vec[0], len);
|
||||
}
|
||||
}
|
||||
SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field) {
|
||||
bst_ulong olen;
|
||||
const float *res = XGDMatrixGetFloatInfo(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(field)), &olen);
|
||||
SEXP ret = PROTECT(allocVector(REALSXP, olen));
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
REAL(ret)[i] = res[i];
|
||||
}
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
// functions related to booster
|
||||
void _BoosterFinalizer(SEXP ext) {
|
||||
if (R_ExternalPtrAddr(ext) == NULL) return;
|
||||
XGBoosterFree(R_ExternalPtrAddr(ext));
|
||||
R_ClearExternalPtr(ext);
|
||||
}
|
||||
SEXP XGBoosterCreate_R(SEXP dmats) {
|
||||
int len = length(dmats);
|
||||
std::vector<void*> dvec;
|
||||
for (int i = 0; i < len; ++i){
|
||||
dvec.push_back(R_ExternalPtrAddr(VECTOR_ELT(dmats, i)));
|
||||
}
|
||||
void *handle = XGBoosterCreate(&dvec[0], dvec.size());
|
||||
SEXP ret = PROTECT(R_MakeExternalPtr(handle, R_NilValue, R_NilValue));
|
||||
R_RegisterCFinalizerEx(ret, _BoosterFinalizer, TRUE);
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGBoosterSetParam_R(SEXP handle, SEXP name, SEXP val) {
|
||||
XGBoosterSetParam(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(name)),
|
||||
CHAR(asChar(val)));
|
||||
}
|
||||
void XGBoosterUpdateOneIter_R(SEXP handle, SEXP iter, SEXP dtrain) {
|
||||
XGBoosterUpdateOneIter(R_ExternalPtrAddr(handle),
|
||||
asInteger(iter),
|
||||
R_ExternalPtrAddr(dtrain));
|
||||
}
|
||||
void XGBoosterBoostOneIter_R(SEXP handle, SEXP dtrain, SEXP grad, SEXP hess) {
|
||||
utils::Check(length(grad) == length(hess), "gradient and hess must have same length");
|
||||
int len = length(grad);
|
||||
std::vector<float> tgrad(len), thess(len);
|
||||
#pragma omp parallel for schedule(static)
|
||||
for (int j = 0; j < len; ++j) {
|
||||
tgrad[j] = REAL(grad)[j];
|
||||
thess[j] = REAL(hess)[j];
|
||||
}
|
||||
XGBoosterBoostOneIter(R_ExternalPtrAddr(handle),
|
||||
R_ExternalPtrAddr(dtrain),
|
||||
&tgrad[0], &thess[0], len);
|
||||
}
|
||||
SEXP XGBoosterEvalOneIter_R(SEXP handle, SEXP iter, SEXP dmats, SEXP evnames) {
|
||||
utils::Check(length(dmats) == length(evnames), "dmats and evnams must have same length");
|
||||
int len = length(dmats);
|
||||
std::vector<void*> vec_dmats;
|
||||
std::vector<std::string> vec_names;
|
||||
std::vector<const char*> vec_sptr;
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec_dmats.push_back(R_ExternalPtrAddr(VECTOR_ELT(dmats, i)));
|
||||
vec_names.push_back(std::string(CHAR(asChar(VECTOR_ELT(evnames, i)))));
|
||||
}
|
||||
for (int i = 0; i < len; ++i) {
|
||||
vec_sptr.push_back(vec_names[i].c_str());
|
||||
}
|
||||
return mkString(XGBoosterEvalOneIter(R_ExternalPtrAddr(handle),
|
||||
asInteger(iter),
|
||||
&vec_dmats[0], &vec_sptr[0], len));
|
||||
}
|
||||
SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin) {
|
||||
bst_ulong olen;
|
||||
const float *res = XGBoosterPredict(R_ExternalPtrAddr(handle),
|
||||
R_ExternalPtrAddr(dmat),
|
||||
asInteger(output_margin),
|
||||
&olen);
|
||||
SEXP ret = PROTECT(allocVector(REALSXP, olen));
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
REAL(ret)[i] = res[i];
|
||||
}
|
||||
UNPROTECT(1);
|
||||
return ret;
|
||||
}
|
||||
void XGBoosterLoadModel_R(SEXP handle, SEXP fname) {
|
||||
XGBoosterLoadModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
|
||||
}
|
||||
void XGBoosterSaveModel_R(SEXP handle, SEXP fname) {
|
||||
XGBoosterSaveModel(R_ExternalPtrAddr(handle), CHAR(asChar(fname)));
|
||||
}
|
||||
void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap) {
|
||||
bst_ulong olen;
|
||||
const char **res = XGBoosterDumpModel(R_ExternalPtrAddr(handle),
|
||||
CHAR(asChar(fmap)),
|
||||
&olen);
|
||||
FILE *fo = utils::FopenCheck(CHAR(asChar(fname)), "w");
|
||||
for (size_t i = 0; i < olen; ++i) {
|
||||
fprintf(fo, "booster[%u]:\n", static_cast<unsigned>(i));
|
||||
fprintf(fo, "%s", res[i]);
|
||||
}
|
||||
fclose(fo);
|
||||
}
|
||||
}
|
||||
124
R-package/src-x64/xgboost_R.h
Normal file
124
R-package/src-x64/xgboost_R.h
Normal file
@ -0,0 +1,124 @@
|
||||
#ifndef XGBOOST_WRAPPER_R_H_
|
||||
#define XGBOOST_WRAPPER_R_H_
|
||||
/*!
|
||||
* \file xgboost_wrapper_R.h
|
||||
* \author Tianqi Chen
|
||||
* \brief R wrapper of xgboost
|
||||
*/
|
||||
extern "C" {
|
||||
#include <Rinternals.h>
|
||||
}
|
||||
|
||||
extern "C" {
|
||||
/*!
|
||||
* \brief load a data matrix
|
||||
* \param fname name of the content
|
||||
* \param silent whether print messages
|
||||
* \return a loaded data matrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromFile_R(SEXP fname, SEXP silent);
|
||||
/*!
|
||||
* \brief create matrix content from dense matrix
|
||||
* This assumes the matrix is stored in column major format
|
||||
* \param data R Matrix object
|
||||
* \param missing which value to represent missing value
|
||||
* \return created dmatrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromMat_R(SEXP mat,
|
||||
SEXP missing);
|
||||
/*!
|
||||
* \brief create a matrix content from CSC format
|
||||
* \param indptr pointer to column headers
|
||||
* \param indices row indices
|
||||
* \param data content of the data
|
||||
* \return created dmatrix
|
||||
*/
|
||||
SEXP XGDMatrixCreateFromCSC_R(SEXP indptr,
|
||||
SEXP indices,
|
||||
SEXP data);
|
||||
/*!
|
||||
* \brief load a data matrix into binary file
|
||||
* \param handle a instance of data matrix
|
||||
* \param fname file name
|
||||
* \param silent print statistics when saving
|
||||
*/
|
||||
void XGDMatrixSaveBinary_R(SEXP handle, SEXP fname, SEXP silent);
|
||||
/*!
|
||||
* \brief set information to dmatrix
|
||||
* \param handle a instance of data matrix
|
||||
* \param field field name, can be label, weight
|
||||
* \param array pointer to float vector
|
||||
*/
|
||||
void XGDMatrixSetInfo_R(SEXP handle, SEXP field, SEXP array);
|
||||
/*!
|
||||
* \brief get info vector from matrix
|
||||
* \param handle a instance of data matrix
|
||||
* \param field field name
|
||||
* \return info vector
|
||||
*/
|
||||
SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field);
|
||||
/*!
|
||||
* \brief create xgboost learner
|
||||
* \param dmats a list of dmatrix handles that will be cached
|
||||
*/
|
||||
SEXP XGBoosterCreate_R(SEXP dmats);
|
||||
/*!
|
||||
* \brief set parameters
|
||||
* \param handle handle
|
||||
* \param name parameter name
|
||||
* \param val value of parameter
|
||||
*/
|
||||
void XGBoosterSetParam_R(SEXP handle, SEXP name, SEXP val);
|
||||
/*!
|
||||
* \brief update the model in one round using dtrain
|
||||
* \param handle handle
|
||||
* \param iter current iteration rounds
|
||||
* \param dtrain training data
|
||||
*/
|
||||
void XGBoosterUpdateOneIter_R(SEXP ext, SEXP iter, SEXP dtrain);
|
||||
/*!
|
||||
* \brief update the model, by directly specify gradient and second order gradient,
|
||||
* this can be used to replace UpdateOneIter, to support customized loss function
|
||||
* \param handle handle
|
||||
* \param dtrain training data
|
||||
* \param grad gradient statistics
|
||||
* \param hess second order gradient statistics
|
||||
*/
|
||||
void XGBoosterBoostOneIter_R(SEXP handle, SEXP dtrain, SEXP grad, SEXP hess);
|
||||
/*!
|
||||
* \brief get evaluation statistics for xgboost
|
||||
* \param handle handle
|
||||
* \param iter current iteration rounds
|
||||
* \param dmats list of handles to dmatrices
|
||||
* \param evname name of evaluation
|
||||
* \return the string containing evaluation stati
|
||||
*/
|
||||
SEXP XGBoosterEvalOneIter_R(SEXP handle, SEXP iter, SEXP dmats, SEXP evnames);
|
||||
/*!
|
||||
* \brief make prediction based on dmat
|
||||
* \param handle handle
|
||||
* \param dmat data matrix
|
||||
* \param output_margin whether only output raw margin value
|
||||
*/
|
||||
SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin);
|
||||
/*!
|
||||
* \brief load model from existing file
|
||||
* \param handle handle
|
||||
* \param fname file name
|
||||
*/
|
||||
void XGBoosterLoadModel_R(SEXP handle, SEXP fname);
|
||||
/*!
|
||||
* \brief save model into existing file
|
||||
* \param handle handle
|
||||
* \param fname file name
|
||||
*/
|
||||
void XGBoosterSaveModel_R(SEXP handle, SEXP fname);
|
||||
/*!
|
||||
* \brief dump model into text file
|
||||
* \param handle handle
|
||||
* \param fname file name of model that can be dumped into
|
||||
* \param fmap name to fmap can be empty string
|
||||
*/
|
||||
void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap);
|
||||
};
|
||||
#endif // XGBOOST_WRAPPER_R_H_
|
||||
Loading…
x
Reference in New Issue
Block a user