original_docstring: Return probabilities using the log-likelihoods in mini-batchs setting.
docstring: Return probabilities using the log-likelihoods in mini-batchs setting.
docstring_tokens: Return probabilities using the log - likelihoods in mini - batchs setting .
code: def predict_proba_many(self, X: pd.DataFrame) -> pd.DataFrame:
          """Return probabilities using the log-likelihoods in mini-batchs setting."""
          jll = self.joint_log_likelihood_many(X)
          if jll.empty:
              return jll
          lse = pd.Series(special.logsumexp(jll, axis=1))
          return np.exp(jll.subtract(lse.values, axis="rows"))
code_tokens: def predict_proba_many ( self , X : pd . DataFrame ) -> pd . DataFrame : jll = self . joint_log_likelihood_many ( X ) if jll . empty : return jll lse = pd . Series ( special . logsumexp ( jll , axis = 1 ) ) return np . exp ( jll . subtract ( lse . values , axis = "rows" ) )
short_docstring: Return probabilities using the log-likelihoods in mini-batchs setting.
short_docstring_tokens: Return probabilities using the log - likelihoods in mini - batchs setting .
comment: """Return probabilities using the log-likelihoods in mini-batchs setting."""