NAME

AI::XGBoost::CAPI::RAW - Perl wrapper for XGBoost C API https://github.com/dmlc/xgboost

VERSION

version 0.11

SYNOPSIS

use 5.010;
use AI::XGBoost::CAPI::RAW;
use FFI::Platypus;

my $silent = 0;
my ($dtrain, $dtest) = (0, 0);

AI::XGBoost::CAPI::RAW::XGDMatrixCreateFromFile('agaricus.txt.test', $silent, \$dtest);
AI::XGBoost::CAPI::RAW::XGDMatrixCreateFromFile('agaricus.txt.train', $silent, \$dtrain);

my ($rows, $cols) = (0, 0);
AI::XGBoost::CAPI::RAW::XGDMatrixNumRow($dtrain, \$rows);
AI::XGBoost::CAPI::RAW::XGDMatrixNumCol($dtrain, \$cols);
say "Dimensions: $rows, $cols";

my $booster = 0;

AI::XGBoost::CAPI::RAW::XGBoosterCreate( [$dtrain] , 1, \$booster);

for my $iter (0 .. 10) {
    AI::XGBoost::CAPI::RAW::XGBoosterUpdateOneIter($booster, $iter, $dtrain);
}

my $out_len = 0;
my $out_result = 0;

AI::XGBoost::CAPI::RAW::XGBoosterPredict($booster, $dtest, 0, 0, \$out_len, \$out_result);
my $ffi = FFI::Platypus->new();
my $predictions = $ffi->cast(opaque => "float[$out_len]", $out_result);

#say join "\n", @$predictions;

AI::XGBoost::CAPI::RAW::XGBoosterFree($booster);
AI::XGBoost::CAPI::RAW::XGDMatrixFree($dtrain);
AI::XGBoost::CAPI::RAW::XGDMatrixFree($dtest);

DESCRIPTION

Wrapper for the C API.

The doc for the methods is extracted from doxygen comments: https://github.com/dmlc/xgboost/blob/master/include/xgboost/c_api.h

FUNCTIONS

XGBGetLastError

Get string message of the last error

All functions in this file will return 0 when success and -1 when an error occurred, XGBGetLastError can be called to retrieve the error

This function is thread safe and can be called by different thread

Returns string error information

XGDMatrixCreateFromFile

Load a data matrix

Parameters:

filename: the name of the file
silent: whether print messages during loading
out: a loaded data matrix

XGDMatrixCreateFromCSREx

Create a matrix content from CSR fromat

Parameters:

indptr: pointer to row headers
indices: findex
data: fvalue
nindptr: number of rows in the matrix + 1
nelem: number of nonzero elements in the matrix
num_col: number of columns; when it's set to 0, then guess from data
out: created dmatrix

XGDMatrixCreateFromCSCEx

Create a matrix content from CSC format

Parameters:

col_ptr: pointer to col headers
indices: findex
data: fvalue
nindptr: number of rows in the matrix + 1
nelem: number of nonzero elements in the matrix
num_row: number of rows; when it's set to 0, then guess from data

XGDMatrixCreateFromMat

Create matrix content from dense matrix

Parameters:

data: pointer to the data space
nrow: number of rows
ncol: number columns
missing: which value to represent missing value
out: created dmatrix

XGDMatrixCreateFromMat_omp

Create matrix content from dense matrix

Parameters:

data: pointer to the data space
nrow: number of rows
ncol: number columns
missing: which value to represent missing value
out: created dmatrix
nthread: number of threads (up to maximum cores available, if <=0 use all cores)

XGDMatrixSliceDMatrix

Create a new dmatrix from sliced content of existing matrix

Parameters:

handle: instance of data matrix to be sliced
idxset: index set
len: length of index set
out: a sliced new matrix

XGDMatrixNumRow

Get number of rows.

Parameters:

handle: the handle to the DMatrix
out: The address to hold number of rows.

XGDMatrixNumCol

Get number of cols.

Parameters:

handle: the handle to the DMatrix
out: The address to hold number of cols.

XGDMatrixSaveBinary

load a data matrix into binary file

Parameters:

handle: a instance of data matrix
fname: file name
silent: print statistics when saving

XGDMatrixSetFloatInfo

Set float vector to a content in info

Parameters:

handle: a instance of data matrix
field: field name, can be label, weight
array: pointer to float vector
len: length of array

XGDMatrixSetUIntInfo

Set uint32 vector to a content in info

Parameters:

handle: a instance of data matrix
field: field name, can be label, weight
array: pointer to unsigned int vector
len: length of array

XGDMatrixSetGroup

Set label of the training matrix

Parameters:

handle: a instance of data matrix
group: pointer to group size
len: length of the array

XGDMatrixGetFloatInfo

Get float info vector from matrix

Parameters:

handle: a instance of data matrix
field: field name
out_len: used to set result length
out_dptr: pointer to the result

XGDMatrixGetUIntInfo

Get uint32 info vector from matrix

Parameters:

handle: a instance of data matrix
field: field name
out_len: The length of the field
out_dptr: pointer to the result

XGDMatrixFree

Free space in data matrix

XGBoosterCreate

Create xgboost learner

Parameters:

dmats: matrices that are set to be cached
len: length of dmats
out: handle to the result booster

XGBoosterFree

Free obj in handle

Parameters:

handle: handle to be freed

XGBoosterSetParam

Update the model in one round using dtrain

Parameters:

handle: handle
name: parameter name
value: value of parameter

XGBoosterBoostOneIter

Update the modelo, by directly specify grandient and second order gradient, this can be used to replace UpdateOneIter, to support customized loss function

Parameters:

handle: handle
dtrain: training data
grad: gradient statistics
hess: second order gradinet statistics
len: length of grad/hess array

XGBoosterUpdateOneIter

Update the model in one round using dtrain

Parameters:

handle: handle
iter: current iteration rounds
dtrain: training data

XGBoosterEvalOneIter

XGBoosterPredict

Make prediction based on dmat

Parameters:

handle

handle

dmat

data matrix

option_mask

bit-mask of options taken in prediction, possible values

0: normal prediction
1: output margin instead of transformed value
2: output leaf index of trees instead of leaf value, note leaf index is unique per tree
4: output feature contributions to individual predictions

ntree_limit

limit number of trees used for prediction, this is only valid for boosted trees when the parameter is set to 0, we will use all the trees

out_len

used to store length of returning result

out_result

used to set a pointer to array

XGBoosterLoadModel

Load model form existing file

Parameters:

handle: handle
fname: file name

XGBoosterSaveModel

Save model into existing file

Parameters:

handle: handle
fname: file name

XGBoosterLoadModelFromBuffer

XGBoosterGetModelRaw

XGBoosterDumpModel

XGBoosterDumpModelEx

XGBoosterDumpModelWithFeatures

XGBoosterDumpModelExWithFeatures

XGBoosterSetAttr

XGBoosterGetAttr

XGBoosterGetAttrNames

XGBoosterLoadRabitCheckpoint

XGBoosterSaveRabitCheckpoint

AUTHOR

Pablo Rodríguez González <pablo.rodriguez.gonzalez@gmail.com>

COPYRIGHT AND LICENSE

To install AI::XGBoost, copy and paste the appropriate command in to your terminal.

cpanm

cpanm AI::XGBoost

CPAN shell

perl -MCPAN -e shell
install AI::XGBoost

For more information on module installation, please visit the detailed CPAN module installation guide.

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NAME

VERSION

SYNOPSIS

DESCRIPTION

FUNCTIONS

XGBGetLastError

XGDMatrixCreateFromFile

XGDMatrixCreateFromCSREx

XGDMatrixCreateFromCSCEx

XGDMatrixCreateFromMat

XGDMatrixCreateFromMat_omp

XGDMatrixSliceDMatrix

XGDMatrixNumRow

XGDMatrixNumCol

XGDMatrixSaveBinary

XGDMatrixSetFloatInfo

XGDMatrixSetUIntInfo

XGDMatrixSetGroup

XGDMatrixGetFloatInfo

XGDMatrixGetUIntInfo

XGDMatrixFree

XGBoosterCreate

XGBoosterFree

XGBoosterSetParam

XGBoosterBoostOneIter

XGBoosterUpdateOneIter

XGBoosterEvalOneIter

XGBoosterPredict

XGBoosterLoadModel

XGBoosterSaveModel

XGBoosterLoadModelFromBuffer

XGBoosterGetModelRaw

XGBoosterDumpModel

XGBoosterDumpModelEx

XGBoosterDumpModelWithFeatures

XGBoosterDumpModelExWithFeatures

XGBoosterSetAttr

XGBoosterGetAttr

XGBoosterGetAttrNames

XGBoosterLoadRabitCheckpoint

XGBoosterSaveRabitCheckpoint

AUTHOR

COPYRIGHT AND LICENSE

Module Install Instructions