ValueError: Expected 1D or 2D array, got 3D array instead

This error message is raised when a function or method is expecting a one-dimensional or two-dimensional array as input, but a three-dimensional array is provided instead.

A 1D array is simply a list of values, while a 2D array is a matrix with rows and columns. A 3D array is a collection of matrices with an additional depth dimension.

To fix this error, you can try reshaping or flattening the 3D array to make it 1D or 2D. Alternatively, you can modify the function or method to accept 3D arrays as input if that is what you need for your specific use case.

相关问题

ValueError: Expected 1D or 2D array, got 0D array instead

This error occurs when you are trying to pass a scalar value (0D array) to a function or method that expects a 1D or 2D array.

For example, if you try to pass a single number to a function that expects an array of numbers, you will get this error.

To fix this error, you need to make sure that you are passing the correct type of input to the function or method. If you need to pass a single value, you can wrap it in an array or use a different function that accepts scalar inputs.

ValueError: Expected 2D array, got 1D array instead:

这个错误通常是因为你的代码中传递给某个函数的是一维数组，但是该函数期望接收二维数组。你需要将传递的数组转换为二维数组。

例如，如果你使用的是scikit-learn库中的某个函数，通常情况下，该函数期望接收一个二维数组，其中每行代表一个样本，每列代表一个特征。如果你只传递了一个一维数组，那么就会出现上述的错误。

要解决这个问题，你可以使用 reshape() 函数将一维数组转换为二维数组，或者使用 numpy 库中的 expand_dims() 函数将其转换为二维数组。

示例代码：

import numpy as np
from sklearn.linear_model import LinearRegression

# 创建一维数组
X = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 6, 8, 10])

# 将 X 转换为二维数组
X = X.reshape(-1, 1)

# 使用线性回归模型拟合数据
model = LinearRegression()
model.fit(X, y)

在上述代码中，我们使用了 reshape() 函数将 X 数组转换为二维数组，并将其传递给 LinearRegression() 函数进行拟合。