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Use fast_logdet to compute penalty #18

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Use fast_logdet to compute penalty #18

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5 changes: 4 additions & 1 deletion firthlogist/firthlogist.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.exceptions import ConvergenceWarning
from sklearn.preprocessing import LabelEncoder
from sklearn.utils.extmath import fast_logdet
from sklearn.utils.multiclass import check_classification_targets
from sklearn.utils.validation import check_is_fitted
from tabulate import tabulate
Expand Down Expand Up @@ -319,7 +320,9 @@ def _loglikelihood(X, y, preds):
# penalized log-likelihood
XW = _get_XW(X, preds)
fisher_info_mtx = XW.T @ XW
penalty = 0.5 * np.log(np.linalg.det(fisher_info_mtx))
penalty = 0.5 * fast_logdet(fisher_info_mtx)
if not np.isfinite(penalty):
penalty = 0
return -1 * (np.sum(y * np.log(preds) + (1 - y) * np.log(1 - preds)) + penalty)


Expand Down