备注
前往末尾 下载完整示例代码。
此脚本演示如何访问评估指标
import os
import xgboost as xgb
CURRENT_DIR = os.path.dirname(__file__)
dtrain = xgb.DMatrix(
os.path.join(CURRENT_DIR, "../data/agaricus.txt.train?format=libsvm")
)
dtest = xgb.DMatrix(
os.path.join(CURRENT_DIR, "../data/agaricus.txt.test?format=libsvm")
)
param = [
("max_depth", 2),
("objective", "binary:logistic"),
("eval_metric", "logloss"),
("eval_metric", "error"),
]
num_round = 2
watchlist = [(dtest, "eval"), (dtrain, "train")]
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist, evals_result=evals_result)
print("Access logloss metric directly from evals_result:")
print(evals_result["eval"]["logloss"])
print("")
print("Access metrics through a loop:")
for e_name, e_mtrs in evals_result.items():
print("- {}".format(e_name))
for e_mtr_name, e_mtr_vals in e_mtrs.items():
print(" - {}".format(e_mtr_name))
print(" - {}".format(e_mtr_vals))
print("")
print("Access complete dictionary:")
print(evals_result)