我正在用子集数据集拟合逻辑回归。拆分数据集并拟合模型后，出现以下错误消息：
/Users/Eddie/anaconda/lib/python3.4/site-packages/sklearn/utils/validation.py:526: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel(). y = column_or_1d(y, warn=True)
所以我target_newrdn = target_newrdn.ravel()用来修改我的目标变量，但这给了我：
AttributeError: 'DataFrame' object has no attribute 'ravel'
我想知道问题出在哪里，如何解决？有人可以帮忙吗？
我的代码：
from sklearn.datasets import fetch_covtype
import numpy as np
import pandas as pd
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split
cov = fetch_covtype()
cov_data = pd.DataFrame(cov.data)
cov_target = pd.DataFrame(cov.target)
data_newrdn = cov_data.head(n=10000)
target_newrdn = cov_target.head(n=10000)
target_newrdn = target_newrdn.ravel() ## I thought this could fix it??
X_train2, X_test2, y_train2, y_test2 = train_test_split(data_newrdn,
target_newrdn, random_state=42)
scaler.fit(X_train2)
X_train_scaled2 = scaler.transform(X_train2)
# Logistic Regression
param_grid = {'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000]}
print(param_grid)
grid = GridSearchCV(LogisticRegression(), param_grid, cv=kfold)
grid.fit(X_train_scaled2, y_train2)
print("Best cross-validation score w/ kfold:
{:.2f}".format(grid.best_score_))
print("Best parameters: ", grid.best_params_)
显然，数据框没有ravel功能。尝试：
target_newrdn.values.ravel()
target_newrdn.values返回一个numpy ndarray，然后执行ravel该操作。注意，这将返回一个展平的numpy数组。您可能需要转换回数据框。
但是我认为您需要flatten()，因为它返回一个副本，所以如果您修改ravel返回的数组，那么它不会修改原始数组中的条目。
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我来说两句