问题描述
在多类分类中使用自定义损失函数时，出现一个错误，即我的自定义目标函数没有calc_ders_range属性。但是，根据我在catboost的Telegram频道中的讨论，calc_ders_range用于单个分类/回归。即使我将自定义目标传递给catboostClassifier，我仍然困惑于以下错误。
我的代码：
输出标签为int64类型，其值从0到25代表26个类别。自Usage Examples的{{3}}样本中获取了自定义目标和准确性指标
class MyObjective(object):
def calc_ders_multi(self,approx,target,weight):
approx = np.array(approx) - max(approx)
exp_approx = np.exp(approx)
exp_sum = exp_approx.sum()
grad = []
hess = []
for j in range(len(approx)):
der1 = -exp_approx[j] / exp_sum
if j == target:
der1 += 1
hess_row = []
for j2 in range(len(approx)):
der2 = exp_approx[j] * exp_approx[j2] / (exp_sum**2)
if j2 == j:
der2 -= exp_approx[j] / exp_sum
hess_row.append(der2 * weight)
grad.append(der1 * weight)
hess.append(hess_row)
return (grad,hess)
class AccuracyMetric(object):
def get_final_error(self,error,weight):
return error / (weight + 1e-38)
def is_max_optimal(self):
return True
def evaluate(self,approxes,weight):
best_class = np.argmax(approxes,axis=0)
accuracy_sum = 0
weight_sum = 0
for i in range(len(target)):
w = 1.0 if weight is None else weight[i]
weight_sum += w
accuracy_sum += w * (best_class[i] == target[i])
return accuracy_sum,weight_sum
def get_pipeline(args):
"""Create a pipeline."""
pipeline_feat1 = Pipeline([
('selector',ColumnSelector(cols='feat1',drop_axis=True)),('vec',TfidfVectorizer(tokenizer=word_tokenize)),])
pipeline_feat2 = Pipeline([
('selector',ColumnSelector(cols='feat2',drop_axis=False)),('imputer',SimpleImputer(missing_values=np.nan,strategy="constant",fill_value=0,copy=False)),('ohe',OneHotEncoder(handle_unkNown='ignore')),])
pipeline_feat3 = Pipeline([
('selector',ColumnSelector(cols='feat3',])
features = FeatureUnion([
('f1',pipeline_feat1),('f2',pipeline_feat2),('f3',pipeline_feat3),])
steps = [
('features',features),('clf',catboostClassifier(task_type='cpu',iterations=5000,random_seed=0,loss_function=MyObjective(),eval_metric=AccuracyMetric(),verbose=100))
]
train_pipeline = Pipeline(steps)
params = {
"features__f1__vec__max_features": args.f1_max_features,"features__f1__vec__ngram_range": (1,args.f1_max_ngram)
}
params = {k: v for k,v in params.items() if v is not None}
train_pipeline.set_params(**params)
return train_pipeline
# Train model.
pipeline = get_pipeline()
# Split train and test data.
X_train,X_val,y_train,y_val = train_test_split(df_train[['feat1','feat2','feat3']],df_train['label'],train_size=0.8,random_state=21)
model = pipeline.fit(X_train,y_train)
错误消息：
AttributeError Traceback (most recent call last)
_catboost.pyx in _catboost._ObjectiveCalcDersRange()
AttributeError: 'MyObjective' object has no attribute 'calc_ders_range'
During handling of the above exception,another exception occurred:
catboostError Traceback (most recent call last)
<ipython-input-12-ea20f154d788> in <module>
10 train_size=0.8,11 random_state=21)
---> 12 model = pipeline.fit(X_train,y_train)
13
/opt/conda/lib/python3.7/site-packages/sklearn/pipeline.py in fit(self,X,y,**fit_params)
333 if self._final_estimator != 'passthrough':
334 fit_params_last_step = fit_params_steps[self.steps[-1][0]]
--> 335 self._final_estimator.fit(Xt,**fit_params_last_step)
336
337 return self
/opt/conda/lib/python3.7/site-packages/catboost/core.py in fit(self,cat_features,text_features,embedding_features,sample_weight,baseline,use_best_model,eval_set,verbose,logging_level,plot,column_description,verbose_eval,metric_period,silent,early_stopping_rounds,save_snapshot,snapshot_file,snapshot_interval,init_model)
4296 self._fit(X,None,4297 eval_set,-> 4298 silent,init_model)
4299 return self
4300
/opt/conda/lib/python3.7/site-packages/catboost/core.py in _fit(self,pairs,group_id,group_weight,subgroup_id,pairs_weight,init_model)
1807 params,1808 allow_clear_pool,-> 1809 train_params["init_model"]
1810 )
1811
/opt/conda/lib/python3.7/site-packages/catboost/core.py in _train(self,train_pool,test_pool,params,allow_clear_pool,init_model)
1256
1257 def _train(self,init_model):
-> 1258 self._object._train(train_pool,init_model._object if init_model else None)
1259 self._set_trained_model_attributes()
1260
_catboost.pyx in _catboost._catboost._train()
_catboost.pyx in _catboost._catboost._train()
catboostError: catboost/python-package/catboost/helpers.cpp:42: Traceback (most recent call last):
File "_catboost.pyx",line 1345,in _catboost._ObjectiveCalcDersRange
AttributeError: 'MyObjective' object has no attribute 'calc_ders_range'
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