在 sklearn.metrics.plot_confusion_matrix 中抑制科学记数法

Question

我试图很好地绘制一个混淆矩阵，所以我遵循了scikit-learn 的新版本 0.22 的内置绘图混淆矩阵函数。但是，我的混淆矩阵值的一个值是 153，但它在混淆矩阵图中显示为 1.5e+02：

按照scikit-learn 的文档，我发现了这个名为 的参数values_format，但我不知道如何操作这个参数以抑制科学记数法。我的代码如下。

from sklearn import svm, datasets
from sklearn.model_selection import train_test_split
from sklearn.metrics import plot_confusion_matrix

# import some data to play with

X = pd.read_csv("datasets/X.csv")
y = pd.read_csv("datasets/y.csv")

class_names = ['Not Fraud (positive)', 'Fraud (negative)']

# Split the data into a training set and a test set
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)

# Run classifier, using a model that is too regularized (C too low) to see
# the impact on the results
logreg = LogisticRegression()
logreg.fit(X_train, y_train)


np.set_printoptions(precision=2)

# Plot non-normalized confusion matrix
titles_options = [("Confusion matrix, without normalization", None),
                  ("Normalized confusion matrix", 'true')]
for title, normalize in titles_options:
    disp = plot_confusion_matrix(logreg, X_test, y_test,
                                 display_labels=class_names,
                                 cmap=plt.cm.Greens,
                                 normalize=normalize, values_format = '{:.5f}'.format)
    disp.ax_.set_title(title)

    print(title)
    print(disp.confusion_matrix)

plt.show()

Answer 1

只需从调用参数声明中删除“.format”和 {} 括号：

disp = plot_confusion_matrix(logreg, X_test, y_test,
                                 display_labels=class_names,
                                 cmap=plt.cm.Greens,
                                 normalize=normalize, values_format = '.5f')

此外，您可以使用'.5g'避免十进制 0

采取从源头

Answer 2

如果有人使用seaborn\xc2\xb4sheatmap来绘制混淆矩阵，并且上面的答案都不起作用。您应该使用 关闭混淆矩阵中的科学计数法，如下seaborn所示fmt='g'：

\n

sns.heatmap(conf_matrix,annot=True, fmt='g')\n

\n

Answer 3

只需传递values_format='' 示例：

plot_confusion_matrix(clf, X_test, Y_test, values_format = '')