class_docstr: Wraps scikitlearn classifiers.
  
  Parameters
  ----------
  strategy : str, default = "LightGBM"
      The choice for the classifier.
      Available strategies = {"LightGBM", "RandomForest", "ExtraTrees",
      "Tree", "Bagging", "AdaBoost" or "Linear"}.
  
  **params : default = None
      Parameters of the corresponding classifier.
      Examples : n_estimators, max_depth...
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docstr: Predicts class log-probabilities for df.
  
  Parameters
  ----------
  df : pandas dataframe of shape = (n, n_features)
      The dataset with numerical features.
  
  Returns
  -------
  y : array of shape = (n, n_classes)
      The log-probabilities for each class
docstr_tok: ["Predicts","class","log-probabilities","for","df",".","Parameters","--","--","--","--","--","df",":","pandas","dataframe","of","shape","=","(","n",",","n_features",")","The","dataset","with","numerical","features",".","Returns","--","--","--","-","y",":","array","of","shape","=","(","n",",","n_classes",")","The","log-probabilities","for","each","class"]
code: def predict_log_proba(self, df):
      """Predicts class log-probabilities for df.
  
      Parameters
      ----------
      df : pandas dataframe of shape = (n, n_features)
          The dataset with numerical features.
  
      Returns
      -------
      y : array of shape = (n, n_classes)
          The log-probabilities for each class
  
      """
      try:
          if not callable(
              getattr(self.__classifier, "predict_log_proba")
          ):
              raise ValueError(
                  "predict_log_proba attribute is not callable"
              )
      except Exception as e:
          raise e
  
      if self.__fitOK:
          # sanity checks
          if (type(df) != pd.SparseDataFrame) and (
              type(df) != pd.DataFrame
          ):
              raise ValueError("df must be a DataFrame")
  
          return self.__classifier.predict_log_proba(df.values)
      else:
          raise ValueError("You must call the fit function before !")
  
imports: import warnings
  from copy import copy
  import numpy
  import pandas
  from sklearn.ensemble import AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, RandomForestClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.tree import DecisionTreeClassifier
  from lightgbm import LGBMClassifier
label_desc: Use image node_id 8 for calling the Classifier obj's underlying member method code with example usage: obj.predict_log_proba(df) and returns: self