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Merge pull request #1 from quansie/quansie-python-training-patch-1

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training.py - pass all eval_metric information to evals_result
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quansie 2015-10-12 14:11:34 +02:00
commit 8a484e990e
1 changed files with 25 additions and 7 deletions
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32
python-package/xgboost/training.py
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@ -56,7 +56,7 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
else: else:
evals_name = [d[1] for d in evals] evals_name = [d[1] for d in evals]
evals_result.clear() evals_result.clear()
evals_result.update({key: [] for key in evals_name}) evals_result.update({key: {} for key in evals_name})
if not early_stopping_rounds: if not early_stopping_rounds:
for i in range(num_boost_round): for i in range(num_boost_round):
@ -71,9 +71,18 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
if verbose_eval: if verbose_eval:
sys.stderr.write(msg + '\n') sys.stderr.write(msg + '\n')
if evals_result is not None: if evals_result is not None:
res = re.findall(":-?([0-9.]+).", msg) res = re.findall("([0-9a-zA-Z@]+[-]*):-?([0-9.]+).", msg)
for key, val in zip(evals_name, res): for key in evals_name:
evals_result[key].append(val) evals_idx = evals_name.index(key)
res_per_eval = len(res) / len(evals_name)
for r in range(res_per_eval):
res_item = res[(evals_idx*res_per_eval) + r]
res_key = res_item[0]
res_val = res_item[1]
if res_key in evals_result[key]:
evals_result[key][res_key].append(res_val)
else:
evals_result[key][res_key] = [res_val]
return bst return bst
else: else:
@ -119,9 +128,18 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
sys.stderr.write(msg + '\n') sys.stderr.write(msg + '\n')
if evals_result is not None: if evals_result is not None:
res = re.findall(":-?([0-9.]+).", msg) res = re.findall("([0-9a-zA-Z@]+[-]*):-?([0-9.]+).", msg)
for key, val in zip(evals_name, res): for key in evals_name:
evals_result[key].append(val) evals_idx = evals_name.index(key)
res_per_eval = len(res) / len(evals_name)
for r in range(res_per_eval):
res_item = res[(evals_idx*res_per_eval) + r]
res_key = res_item[0]
res_val = res_item[1]
if res_key in evals_result[key]:
evals_result[key][res_key].append(res_val)
else:
evals_result[key][res_key] = [res_val]
score = float(msg.rsplit(':', 1)[1]) score = float(msg.rsplit(':', 1)[1])
if (maximize_score and score > best_score) or \ if (maximize_score and score > best_score) or \