valueerror found input variables with inconsistent numbers of samples 40 10

0 votes

Here I was creating a model based on multiple linear regression, but now I stuck with an error that is " value error: found input variables with inconsistent numbers of samples: [40, 10]

here I am showing you my code.

I am confused, where should I make changes?

in case of assigning the dependent and independent variable to x and y. When I checked y.shape it gives one-dimensional array instead of this it should show two-dimensional array. You can see the whole code as I have given below and screenshots.

import pandas as pd
import numpy as np
import matplotlib.pyplot as mt
dataset = pd.read_csv("50_Startups.csv")
x = dataset.iloc[ :, :-1].values
y = dataset.iloc[ :, 4].values
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
ct = ColumnTransformer( transformers = [('encoder', OneHotEncoder(),[3])], remainder = 'passthrough')
x = np.array(ct.fit_transform(x))
from sklearn.model_selection import train_test_split
x_train, y_train, x_test, y_test = train_test_split( x, y, test_size = 0.2, random_state = 0 )
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit( x_train, y_train )
Jul 21, 2020 in Machine Learning by Monish
• 120 points

edited Jul 21, 2020 by MD 14,404 views

2 answers to this question.

0 votes

Hi@Monish,

Here you used x as your feature parameter and y as your predictor. But your feature parameter should not be 1D. So check the shape of x and if it is 1D, then convert it from 1D to 2D.

$ x.shape
$ x.reshape(-1,1)

Hope this will help you.

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answered Jul 21, 2020 by MD
• 95,440 points
but my x is not 1D ...in my code y is showing it is 1D.....

Hi,

You misplaced in your split section. You have written this below line.

x_train, y_train, x_test, y_test = train_test_split( x, y, test_size = 0.2, random_state = 0 )

But it should be written as given below.

x_train,x_test,y_tarin, y_test = train_test_split( x, y, test_size = 0.2, random_state = 0 )
okk..i made changes as u said...i change the sequence while train test split...but still it showing same problem....
Check once again. I tried with the same code with the same dataset. It is working fine.
yes you figure it out correctly thank you for help!
0 votes
keep random_state =42 in train_test_split module
answered Aug 27, 2020 by sairam
• 160 points
Hi@sairam,

I don't think so. Either you specify random_state or not, it will work. This has a different meaning. If you specify then it will take random value from your dataset.

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