class_docstr: Base Naive Bayes class.
class_docstr_tok: ["Base","Naive","Bayes","class","."]
docstr: Compute the unnormalized posterior log-likelihood of x in mini-batches.
  
  The log-likelihood is `log P(c) + log P(x|c)`.
docstr_tok: ["Compute","the","unnormalized","posterior","log-likelihood","of","x","in","mini-batches",".","The","log-likelihood","is","`","log","P","(","c",")","+","log","P","(","x|c",")","`","."]
code: def joint_log_likelihood_many(self, X: pd.DataFrame) -> pd.DataFrame:
      """Compute the unnormalized posterior log-likelihood of x in mini-batches.
  
      The log-likelihood is `log P(c) + log P(x|c)`.
  
      """
  
file_path: river/river/naive_bayes/base.py
imports: from __future__ import annotations
  import abc
  import math
  import numpy
  import pandas
  from scipy import sparse, special
  from river import base
label_desc: Use image node_id 2 for calling the BaseNB obj's underlying member method code with example usage: obj.joint_log_likelihood_many(X) without return types