SlimRegressor error

[ukamath]

When I run SlimRegressor on a regression data
from imodels import SLIMRegressor
model = SLIMRegressor()
for lambda_reg in [0, 1e-2, 5e-2, 1e-1, 1, 2]:
model.fit(X_train, y_train, lambda_reg)
mse = np.mean(np.square(y_train - model.predict(X_train)))
print(f'lambda: {lambda_reg}\tmse: {mse: 0.2f}\tweights: {model.model.coef_}')

I get

SolverError: Either candidate conic solvers (['GLPK_MI']) do not support the cones output by the problem (SOC, NonNeg), or there are not enough constraints in the problem.

During handling of the above exception, another exception occurred:

TypeError Traceback (most recent call last)
in
2 model = SLIMRegressor()
3 for lambda_reg in [0, 1e-2, 5e-2, 1e-1, 1, 2]:
----> 4 model.fit(X_train, y_train, lambda_reg)
5 mse = np.mean(np.square(y_train - model.predict(X_train)))
6 print(f'lambda: {lambda_reg}\tmse: {mse: 0.2f}\tweights: {model.model.coef_}')

~/opt/anaconda3/lib/python3.7/site-packages/imodels/algebraic/slim.py in fit(self, X, y, lambda_reg, sample_weight)
58 except:
59 m = Lasso(alpha=lambda_reg)
---> 60 m.fit(X, y, sample_weight=sample_weight)
61 self.model.coef_ = np.round(m.coef_).astype(np.int)
62 self.model.intercept_ = m.intercept_

TypeError: fit() got an unexpected keyword argument 'sample_weight'

[csinva]

Thanks for your interest and pointing this out!

The issue here is that your scikit-learn version is < 0.23. To fix this, you'll have to upgrade it to 0.23 or higher. We'll add this to the requirements!