什么是coef_.t？使用t的目的
COEF_用于在Python中的线性方程中找到系数。但是我找不到答案的coef_被放在.t的末尾。这里的.T功能是什么？
for C, marker in zip([0.001, 1, 100], ['o', '^', 'v']):
lr_l1 = LogisticRegression(C=C, penalty="l1").fit(X_train, y_train)
print("Training accuracy of l1 logreg with C={:.3f}: {:.2f}".format(
C, lr_l1.score(X_train, y_train)))
print("Test accuracy of l1 logreg with C={:.3f}: {:.2f}".format(
C, lr_l1.score(X_test, y_test)))
plt.plot(lr_l1.coef_.T, marker, label="C={:.3f}".format(C))
Coef_ is used to find coefficients in linear equations in Python. But Coef_, which I could not find the answer to, was put at the end of .T. What is the .T function here?
for C, marker in zip([0.001, 1, 100], ['o', '^', 'v']):
lr_l1 = LogisticRegression(C=C, penalty="l1").fit(X_train, y_train)
print("Training accuracy of l1 logreg with C={:.3f}: {:.2f}".format(
C, lr_l1.score(X_train, y_train)))
print("Test accuracy of l1 logreg with C={:.3f}: {:.2f}".format(
C, lr_l1.score(X_test, y_test)))
plt.plot(lr_l1.coef_.T, marker, label="C={:.3f}".format(C))
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“ .t”方法表示 transpose 切换行＆amp;列，
如果您有矩阵 m ：
然后 mt 是：
看起来它在这一行中使用：
确保它以预期的方式绘制系数。如果该模型是根据Sklearn LogisticRecrys构建的，则可以查看文档在这里
COEF_具有形状（n_classes，n_features），所以这意味着
COEF_.T具有形状（n_features，n_classes）
在这里是一本笔记本，显示了它的工作原理
".T" method means Transpose which switches rows & columns
if you have a matrix m:
Then m.T would be:
It looks like its used in this line:
to make sure it plots the coefficients in an expected way. If the model was built from sklearn LogisticRegression, then you can review the docs here
coef_ has shape (n_classes,n_features), so that means
coef_.T has shape (n_features,n_classes)
Here is a notebook that shows how this works