Matplotlib 如何设置绘图矩阵中的数字格式

Matplotlib 如何设置绘图矩阵中的数字格式,matplotlib,plot,model,Matplotlib,Plot,Model,如何改进矩阵中这种奇怪、难以辨认的数字格式,使其只显示简单的数字 from sklearn.naive_bayes import GaussianNB from sklearn.linear_model import LogisticRegression from sklearn.ensemble import GradientBoostingClassifier from sklearn.ensemble import RandomForestClassifier from lightgbm

如何改进矩阵中这种奇怪、难以辨认的数字格式,使其只显示简单的数字

from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.ensemble import RandomForestClassifier
from lightgbm import LGBMClassifier
from sklearn.ensemble import RandomForestClassifier

NBC = GaussianNB() 
LRE = LogisticRegression(solver='lbfgs')
GBC = GradientBoostingClassifier()
RFC = RandomForestClassifier()
LGBM = LGBMClassifier()
CBC = CatBoostClassifier(verbose=0, n_estimators=100)


classifiers = [NBC,LRE,GBC,RFC,LGBM,CBC]


for cls in classifiers:
    cls.fit(X_train, y_train)


fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(10,6))
target_names = ['0','1']


for cls, ax in zip(classifiers, axes.flatten()):
    plot_confusion_matrix(cls, 
                          X_test, 
                          y_test, 
                          ax=ax, 
                          cmap='Reds',
                         display_labels=target_names)
    ax.title.set_text(type(cls).__name__)
    
plt.tight_layout()  
plt.show()

尝试将空白值格式作为参数传递给
绘图矩阵
。国家

值\u格式:str,默认值=None

混淆矩阵中值的格式规范。如果没有,则格式规范为“d”或“.2g”,以较短者为准

绘制混乱矩阵(cls,X检验,y检验,ax=ax,cmap='Reds',
显示\u标签=目标\u名称,

values_format='')#尝试将空白值格式作为参数传递给
绘图矩阵
。国家

值\u格式:str,默认值=None

混淆矩阵中值的格式规范。如果没有,则格式规范为“d”或“.2g”,以较短者为准

绘制混乱矩阵(cls,X检验,y检验,ax=ax,cmap='Reds',
显示\u标签=目标\u名称,
值(格式=“”)#
plot_confusion_matrix(cls, X_test, y_test, ax=ax, cmap='Reds',
                     display_labels=target_names,
                     values_format='') # <--------- Passed here