Linear Regression Model predict function not working

Question

I have this code. It basically works all the way until I try to use predict(x-value) to get the y-value answer.

The code is below.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

df = pd.read_csv('linear_data.csv')
x = df.iloc[:,:-1].values
y = df.iloc[:,1:].values
x_train, x_test, y_train, y_test= train_test_split(x,y,test_size=1/3,random_state=0)
reg = LinearRegression()
reg.fit(x_train, y_train)

y_predict = reg.predict(x_test)

y_predict_res = reg.predict(11) --> #This is the error! 11 is the number of years to predict the salary
print(y_predict_res)

The error I get is:

ValueError: Expected 2D array, got scalar array instead: array=11. 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.

The error message doesn't help me much as I don't understand why I need to reshape it.

Does this answer your question? [Error in Python script "Expected 2D array, got 1D array instead:"?](https://stackoverflow.com/questions/45554008/error-in-python-script-expected-2d-array-got-1d-array-instead) see my answer there — Ofer Sadan, Dec 12 '19 at 11:47

score 2 · Answer 1 · answered Dec 12 '19 at 11:51

2

Please note here that the parameter X it is expecting is array_like or sparse matrix, shape (n_samples, n_features), meaning it can't be an individual number. The number/value has to be part of an array.

answered Dec 12 '19 at 11:51

Vlad

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Linear Regression Model predict function not working

1 Answers1