I am trying to train an XGBoost algorithm and I get the following warning :
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.
Is this something I should worry about?
This is my code:
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')
question from:
https://stackoverflow.com/questions/65902818/xgboost-warning-this-may-not-be-accurate 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…