Python 尝试获取回归摘要时出错

我试图进行山脊回归，就像这样：

from sklearn.linear_model import LinearRegression, RidgeCV, Ridge
from regressors import stats

alphas = np.linspace(.00001, 100, 1000)

rr_scaled = RidgeCV(alphas= alphas, cv=5, normalize=True)

rr_scaled.fit(X_train, y_train)

它工作得很好，所以我去获取摘要：

stats.summary(rr_scaled, X_train, y_train)

但我一直在犯这样的错误：

ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 1 and the array at index 1 has size 10

那是什么？语法有问题吗

---

我发现了这篇帖子：但它和我当时做的一模一样。并且在岗位上工作

问题似乎是希望您的数据处于特定的形状。特别是，它似乎期望您的目标变量是一个数组，而不是一个矩阵

考虑以下基于代码的示例：

import numpy as np
import pandas as pd
from regressors import stats
from sklearn.linear_model import LinearRegression, RidgeCV, Ridge

n_features = 3
n_samples = 10
X_train = np.random.normal(0, 1, size=(n_samples, n_features))
y_train = np.random.randn(n_samples)

alphas = np.linspace(.00001, 100, 1000)

rr_scaled = RidgeCV(alphas=alphas, cv=5, normalize=True)
rr_scaled.fit(X_train, y_train)

stats.summary(rr_scaled, X_train, y_train)

如果我运行它，它将执行良好并输出

Residuals:
    Min      1Q  Median    3Q     Max
-2.5431 -0.8815 -0.0059  0.69  2.2218


Coefficients:
            Estimate  Std. Error  t value   p value
_intercept  0.213519    0.463767   0.4604  0.656149
x1          0.001617    0.761174   0.0021  0.998351
x2          0.006398    0.895701   0.0071  0.994457
x3         -0.003119    0.518982  -0.0060  0.995335
---
R-squared:  0.00267,    Adjusted R-squared:  -0.49599
F-statistic: 0.01 on 3 features

现在，如果我将目标更改为“矩阵”形状：

我得到了与您相同的错误：

Traceback (most recent call last):
  File "a.py", line 16, in <module>
    stats.summary(rr_scaled, X_train, y_train)
  File "lib/python3.8/site-packages/regressors/stats.py", line 252, in summary
    coef_df['Estimate'] = np.concatenate(
  File "<__array_function__ internals>", line 5, in concatenate
ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 1 and the array at index 1 has size 3

---

您可以展示一些数据示例吗？首先想到的是，您的训练数组的结构对于

stats.summary

无效。我也检查过了，它说明函数的第一个参数应该是

线性模型

。我不确定它是否与岭回归模型相同，请注意它。@Tino好吧，那么我提到的帖子是错的？@griggy这是机密。。。

Traceback (most recent call last):
  File "a.py", line 16, in <module>
    stats.summary(rr_scaled, X_train, y_train)
  File "lib/python3.8/site-packages/regressors/stats.py", line 252, in summary
    coef_df['Estimate'] = np.concatenate(
  File "<__array_function__ internals>", line 5, in concatenate
ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 1 and the array at index 1 has size 3

y_train = y_train.reshape((-1,))