!pip install xgboost
Requirement already satisfied: xgboost in /usr/local/lib/python3.6/dist-packages (1.5.0)
Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from xgboost) (1.19.5)
Requirement already satisfied: scipy in /shared-libs/python3.6/py/lib/python3.6/site-packages (from xgboost) (1.5.4)
WARNING: You are using pip version 20.2.4; however, version 21.3.1 is available.
You should consider upgrading via the '/usr/bin/python3 -m pip install --upgrade pip' command.
import xgboost as xgb
# read in data
dtrain = xgb.DMatrix('xgboost/demo/data/agaricus.txt.train')
dtest = xgb.DMatrix('xgboost/demo/data/agaricus.txt.test')
# specify parameters via map
param = {'max_depth':2, 'eta':1, 'objective':'binary:logistic' }
num_round = 2
bst = xgb.train(param, dtrain, num_round)
# make prediction
preds = bst.predict(dtest)
preds
[20:14:04] WARNING: ../src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.