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?
- 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.
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_)