python - 使用 OneHotEncoder 错误 "Expected 2D array, got 1D array instead"

Question

我是机器学习的新手，正在尝试解决我在使用 OneHotEncoder 类时遇到的错误。错误是:“预期的二维数组，得到的是一维数组”。所以当我想到一维数组时，它类似于:[1,4,5,6] 而二维数组将是 [[2,3], [3,4], [ 5,6]]，但我仍然无法弄清楚为什么会失败。它在这条线上失败了:

X[:, 0] = onehotencoder1.fit_transform(X[:, 0]).toarray()

这是我的全部代码:

# Import Libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Import Dataset
dataset = pd.read_csv('Data2.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 5].values
df_X = pd.DataFrame(X)
df_y = pd.DataFrame(y)

# Replace Missing Values
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values = 'NaN', strategy = 'mean', axis = 0)
imputer = imputer.fit(X[:, 3:5 ])
X[:, 3:5] = imputer.transform(X[:, 3:5])


# Encoding Categorical Data "Name"
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_x = LabelEncoder()
X[:, 0] = labelencoder_x.fit_transform(X[:, 0])

# Transform into a Matrix
onehotencoder1 = OneHotEncoder(categorical_features = [0])
X[:, 0] = onehotencoder1.fit_transform(X[:, 0]).toarray()

# Encoding Categorical Data "University"
from sklearn.preprocessing import LabelEncoder
labelencoder_x1 = LabelEncoder()
X[:, 1] = labelencoder_x1.fit_transform(X[:, 1])

我相信您可以通过这段代码看出我有 2 列是标签。我使用标签编码器将这些列转换为数字。我想使用 OneHotEncoder 更进一步，将它们变成一个矩阵，这样每一行都会有这样的东西:

0  1  0
1  0  1

唯一想到的是我如何对标签进行编码。我一个一个地做，而不是一次全部做。不确定这是问题所在。

我希望做这样的事情:

# Encoding Categorical Data "Name"
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_x = LabelEncoder()
X[:, 0] = labelencoder_x.fit_transform(X[:, 0])

# Transform into a Matrix
onehotencoder1 = OneHotEncoder(categorical_features = [0])
X[:, 0] = onehotencoder1.fit_transform(X[:, 0]).toarray()

# Encoding Categorical Data "University"
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_x1 = LabelEncoder()
X[:, 1] = labelencoder_x1.fit_transform(X[:, 1])

# Transform into a Matrix
onehotencoder2 = OneHotEncoder(categorical_features = [1])
X[:, 1] = onehotencoder1.fit_transform(X[:, 1]).toarray()

下面你会发现我的全部错误:

File "/Users/jim/anaconda3/lib/python3.6/site-packages/sklearn/utils/validation.py", line 441, in check_array
    "if it contains a single sample.".format(array))

ValueError: Expected 2D array, got 1D array instead:
array=[ 2.  1.  3.  2.  3.  5.  5.  0.  4.  0.].
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.

在正确方向上的任何帮助都会很棒。

Answer 1

我得到了同样的错误，在错误消息之后有如下建议:

"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."

因为我的数据是一个数组，所以我使用了 X.values.reshape(-1,1) 并且它有效。 (还有另一个建议使用 X.values.reshape 而不是 X.reshape)。