培训集中的培训数据
培训集中的培训数据
提问于 2020-01-31 14:46:48
Am，试图使用scikit-学习在我的培训集中训练一个模型，但是得到了这个错误：
ValueError: Expected 2D array, got 1D array instead: array=[90. 4.].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.步骤1:将x和y分割成训练和测试集
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.4, random_state = 4)检查新分割的x值的形状(培训和测试)
X_train = X_train.shape
X_test = X_test.shape
print(X_train)
print(X_test)检查新分割y值的形状(培训和测试)
y_train = y_train.shape
y_test = y_test.shape
print(y_train)
print(y_test)第二步:在培训集上培训我们的模型(使用物流回归)
logR = LogisticRegression()
logR = logR.fit(X_train, y_train)运行这段代码我得到了错误
回答 2
Stack Overflow用户
回答已采纳
发布于 2020-01-31 14:54:58
似乎您正在用数据点的形状替换数据点：
X_train = X_train.shape
X_test = X_test.shape
y_train = y_train.shape
y_test = y_test.shape删除这些行并重新运行。
Stack Overflow用户
发布于 2020-01-31 15:04:06
你做了很棒的工作，但是你做了一件错误的事情:你用它们的形状来替换训练和测试数据，这就是你面临这个错误的原因
#replace these line
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.4, random_state = 4)
print( X_train.shape)
print( X_test.shape)
print(y_train.shape)
print(y_test.shape)
logR = LogisticRegression()
logR = logR.fit(X_train, y_train)
# Now it work fine页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/60006087
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