I have the code below in python to create LinearRegression model. When I train the model with re-sampled data, I get different values for its coefficients. I can't understand why that happens. Can you help me in this please? 

[Update]

* I assume that resampling is the same as shuffling. And that means the order of the data is changed but not the data itself.
* In the use case presented, the number of rows are are the same as I inspected it and as I understand the order of the data is changed.

Thanks!


    
    from sklearn.linear_model import LinearRegression
    from sklearn.utils import resample
    
    model = LinearRegression(fit_intercept=False)
    
    model.fit(X, y)
    print('model.coef_',model.coef_)
    
    model.fit(*resample(X, y))
    print('model.coef_',model.coef_)
    
    model.fit(*resample(X, y))
    print('model.coef_',model.coef_)