Python Linear Regression Predict Error - Array Issue

Question

When I try to use .predict on my linear regression, I get thrown the following error:

ValueError: Expected 2D array, got scalar array instead: array=80. 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.

I don't really understand the reshape feature and why its needed. Can somebody please explain to me what this does, and how to apply it to get a prediction for my model?

import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import LinearRegression

x = np.array([95,85,80,70,60])
y = np.array([85,95,70,65,70])
x = x.reshape(-1,1)
y = y.reshape(-1,1)
plt.scatter(x,y)
plt.show()

reg = LinearRegression()
reg.fit(x,y)

reg.predict(80)

deadshot deadshot · Accepted Answer · 2020-04-23T21:47:33

input of predict() is 2d array you are passing integer value that's why you are getting error. You need to pass 80 as a 2d list [[80]]

reg.predict([[80]])

Python Linear Regression Predict Error - Array Issue

1 Answers