Matplotlib 如何设置绘图矩阵中的数字格式
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
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