Cannot access model attributes when arms are floats

[Daniel8hen]

I've been trying to access an sklearn's model coefficients and got an AttributeError, it seems like something modifies the base model.

This issue gets resolved if the arms are integers.

Minimal code that causes the exception:

import numpy as np
from contextualbandits import online as cb
from sklearn.naive_bayes import BernoulliNB
aa = np.array([0.2, 0.1, 0.2, 0.1, 0.4, 1.1, 0.3, 0.5, 0.6, 0.7])
XX = np.array([[1, 0, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0],
       [0, 1, 0]])
rr = np.array([0, 0, 1, 1, 1, 1, 1, 1, 1, 1])
n_arms = len({t for t in aa})
model = cb.SeparateClassifiers(BernoulliNB(), n_arms, batch_train=True)
model.partial_fit(XX, aa, rr)
[m.coef_ for m in model._oracles.algos]

[david-cortes]

Those floats are interpreted as integers and all of them get cast to zero, so only the first one is fitted. If you want to use non-integer IDs, you need to pass those under nchoices.