This repository was archived by the owner on Dec 6, 2023. It is now read-only.
This repository was archived by the owner on Dec 6, 2023. It is now read-only.
FistaRegressor does not converge for real data #151
Description
I can get the FistaRegressor to converge when data is trivial. The code for the simulated data is below.
from scipy import stats
N, P = 300, 30
m_true = np.zeros(P)
m_true[:4] = [2, -2, 2, 3]
noise = 3 * stats.norm().rvs(N)
data = 3*stats.norm().rvs((N, P))
target = data @ m_true + noise
fista = FistaRegressor(
C=1/n,
penalty='l1',
alpha=lam, # The same alpha LassoCV.alpha_ finds
max_iter=1000,
max_steps=1000,
)
fista.fit(data, target)
(X axis are the individual coefficients and the Y axis are the fitted coef magnitude)
But if I use real data I cannot get it to converge at all.
from statsmodels.tools.tools import add_constant
from sklearn.datasets import load_boston
data, target = load_boston(return_X_y=True)
data = add_constant(data)
(X axis are the individual coefficients and the Y axis are the fitted coef magnitude)
I assume it has something to do with feature scaling but I'm not sure.