如何解决XGBoost 警告这可能不准确
我正在尝试训练 XGBoost 算法,但收到以下警告:
This may not be accurate due to some parameters are only used in language bindings but
passed down to XGBoost core. Or some parameters are not used but slip through this
verification. Please open an issue if you find above cases.
这是我应该担心的事情吗?
这是我的代码:
df_train = pd.read_csv("FullEugFinal.csv ")
y_train = df_train.loc[:,'CLASS']
x_train = df_train.loc[:,'F2ND': 'RMS39']
model = XGBClassifier()
estimators = []
estimators.append(('standardize',StandardScaler()))
estimators.append(('xgb',XGBClassifier(silent=False,n_jobs=1,scale_pos_weight=1,learning_rate=0.009,colsample_bytree = 0.4,subsample = 0.8,objective='binary:logistic',n_estimators=1100,reg_alpha = 0.3,max_depth=4,gamma=0)))
model = Pipeline(estimators)
# define evaluation procedure
kfold = RepeatedStratifiedKFold(n_splits=10,n_repeats=3,random_state=6)
cv_relusts = cross_val_score(model,x_train,y_train,cv=kfold,scoring='accuracy')
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