xgboost train code

gistfile1.txt

import xgboost as xgb
import random
features2d = []
targets = []
for i in range(10):
    features = []
    for j in range(10):
        feature = random.random()
        features.append(feature)
    features2d.append(features)
    target = random.random()
    targets.append(target)
dtrain = xgb.DMatrix(features2d, label=targets)
param = {'max_depth': 3, 'eta': 0.025, 'objective': 'reg:squarederror'}
num_round = 300
tree = xgb.train(param, dtrain, num_round)
tree.save_model("tree.json")