Hello,

I am trying to run the following Linear Regression code and I am getting the error as listed in the subject line. I have tried to research on the given error but I have not been able to figure out the reason.

Error that I am getting is

```
shapes (1,1705) and (2,) not aligned: 1705 (dim 1) != 2 (dim 0)
```

code is as follows

```
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from sklearn.model_selection import train_test_split
#import test and train file
from sklearn.linear_model import LinearRegression
train = pd.read_csv('Train_Data.csv')
#test = pd.read_csv('test.csv')
lreg = LinearRegression()
X = train.loc[:,['Outlet_Establishment_Year','Item_MRP']] # splitting into training and cv for cross validation
x_train, x_cv, y_train, y_cv = train_test_split(X,train.Item_Outlet_Sales,test_size=0.20,random_state=42)
lreg.fit(x_train,y_train) # training the model
pred = lreg.predict(x_cv) # predicting on cv
mse = np.mean((pred - y_cv)**2) # calculating mse
print("MSE=",mse)
# calculating coefficients
coeff = DataFrame(x_train.columns)
coeff['Coefficient Estimate'] = Series(lreg.coef_)
print(coeff[[0,"Coefficient Estimate"]])
y_cv_matrix=y_cv.as_matrix()
print(lreg.score(pred,y_cv_matrix)) # this line not working
```

I have tried to reshape and use np.newaxis as well but it doesnâ€™t work

All the help is appreciated.

Thanks in advance

Mohit