python - 预期的二维数组，得到一维数组而不是错误

Question

我收到错误为

“ValueError：预期的 2D 数组，得到 1D 数组：array=[ 45000. 50000. 60000. 80000. 110000. 150000. 200000. 300000. 500000. 1000000.]。使用 array.reshape(-1, 1) 重塑数据) 如果您的数据具有单个特征或 array.reshape(1, -1) 如果它包含单个样本。"

在执行以下代码时：

# SVR

# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Importing the dataset
dataset = pd.read_csv('Position_S.csv')
X = dataset.iloc[:, 1:2].values
y = dataset.iloc[:, 2].values

 # Feature Scaling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
sc_y = StandardScaler()
X = sc_X.fit_transform(X)
y = sc_y.fit_transform(y)

# Fitting SVR to the dataset
from sklearn.svm import SVR
regressor = SVR(kernel = 'rbf')
regressor.fit(X, y)

# Visualising the SVR results
plt.scatter(X, y, color = 'red')
plt.plot(X, regressor.predict(X), color = 'blue')
plt.title('Truth or Bluff (SVR)')
plt.xlabel('Position level')
plt.ylabel('Salary')
plt.show()

# Visualising the SVR results (for higher resolution and smoother curve)
X_grid = np.arange(min(X), max(X), 0.01)
X_grid = X_grid.reshape((len(X_grid), 1))
plt.scatter(X, y, color = 'red')
plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')
plt.title('Truth or Bluff (SVR)')
plt.xlabel('Position level')
plt.ylabel('Salary')
plt.show()

标签： pythonmachine-learningdata-science

Answer 1

似乎，预期的尺寸是错误的。你能试试：

regressor = SVR(kernel='rbf')
regressor.fit(X.reshape(-1, 1), y)