Question

我正在尝试构建一种方法来绘制不同ML模型（例如

）的准确性

from sklearn import model_selection
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier

我已使用此代码，但无法获得条形图

#Evaluating performance
results = []
names = []
scoring = 'accuracy'

for name, model in models:
    kfold = model_selection.KFold(n_splits=10, random_state=0)
    cv_results = model_selection.cross_val_score(model, X_train, y_train, cv=kfold, scoring=scoring)
    results.append(cv_results)
    names.append(name)
    msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
    results.append(cv_results.mean())
    print(msg)

plt.plot(cv_results) plots a line graph

我正在尝试绘制X轴（不同模型）Y轴（精度）的条形图

Answer 1

plt.plot将按照您的指示绘制线条。您需要的是plt.bar，它将绘制一个小节图。假设模型的名称存储在列表names中，准确度存储在列表results中，就像您的代码片段一样，则应该这样做：

plt.bar(names,results)

比较不同型号的精度

1 个答案: