How to implement logistic regression in xgboost (Python)?

Question

Python

There is a tutorial :

import xgboost as xgb
# read in data
dtrain = xgb.DMatrix('demo/data/agaricus.txt.train')
dtest = xgb.DMatrix('demo/data/agaricus.txt.test')
# specify parameters via map
param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
num_round = 2
bst = xgb.train(param, dtrain, num_round)
# make prediction
preds = bst.predict(dtest)

But it is not clear what the agaricus.txt format is. How to implement logregression in xgboost? An example, if not difficult.

Answer 1

xgboost.readthedocs.io/en/latest/python/python_api.html
Create DMatrix from ndarray)
Well, xgboost is not a logistic regression)