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_)
