NAME
AI::XGBoost::CAPI - Perl wrapper for XGBoost C API https://github.com/dmlc/xgboost
VERSION
version 0.006
SYNOPSIS
use 5.010;
use AI::XGBoost::CAPI qw(:all);
my $dtrain = XGDMatrixCreateFromFile('agaricus.txt.train');
my $dtest = XGDMatrixCreateFromFile('agaricus.txt.test');
my ($rows, $cols) = (XGDMatrixNumRow($dtrain), XGDMatrixNumCol($dtrain));
say "Train dimensions: $rows, $cols";
my $booster = XGBoosterCreate([$dtrain]);
for my $iter (0 .. 10) {
XGBoosterUpdateOneIter($booster, $iter, $dtrain);
}
my $predictions = XGBoosterPredict($booster, $dtest);
# say join "\n", @$predictions;
XGBoosterFree($booster);
XGDMatrixFree($dtrain);
XGDMatrixFree($dtest);DESCRIPTION
Perlified wrapper for the C API
Error handling
XGBoost c api functions returns some int to signal the presence/absence of error. In this module that is achieved using Exceptions from Exception::Class
FUNCTIONS
XGDMatrixCreateFromFile
Load a data matrix
Parameters:
- filename
-
the name of the file
- silent
-
whether print messages during loading
Returns a loaded data matrix
XGDMatrixCreateFromMat
Create from dense matrix
Parameters:
- matrix
-
matrix data
- missing
-
value indicating missing data (optional)
Returns a loaded data matrix
XGDMatrixNumRow
Get number of rows
Parameters:
- matrix
-
DMatrix
XGDMatrixNumCol
Get number of cols
Parameters:
- matrix
-
DMatrix
XGDMatrixSetFloatInfo
XGDMatrixGetFloatInfo
XGDMatrixFree
Free space in data matrix
Parameters:
- matrix
-
DMatrix to be freed
XGBoosterCreate
Create XGBoost learner
Parameters:
- matrices
-
matrices that are set to be cached
XGBoosterSetParam
XGBoosterSetAttr
XGBoosterGetAttr
XGBoosterGetAttrNames
XGBoosterUpdateOneIter
Update the model in one round using train matrix
Parameters:
- booster
-
XGBoost learner to train
- iter
-
current iteration rounds
- train_matrix
-
training data
XGBoosterBoostOneIter
XGBoosterEvalOneIter
XGBoosterPredict
Make prediction based on train matrix
Parameters:
- booster
-
XGBoost learner
- data_matrix
-
Data matrix with the elements to predict
- 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
Returns an arrayref with the predictions corresponding to the rows of data matrix
XGBoosterDumpModel
XGBoosterDumpModelEx
XGBoosterDumpModelWithFeatures
XGBoosterDumpModelExWithFeatures
XGBoosterFree
Free booster object
Parameters:
- booster
-
booster to be freed
AUTHOR
Pablo Rodríguez González <pablo.rodriguez.gonzalez@gmail.com>
COPYRIGHT AND LICENSE
This software is Copyright (c) 2017 by Pablo Rodríguez González.
This is free software, licensed under:
The Apache License, Version 2.0, January 2004