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...
class_docstr_tok: ["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","..."]
docstr: Init Classifier object.
  
  User can define strategy parameters.
  
  Parameters
  ----------
  strategy : str, default = "LightGBM"
      The choice of the classifier.
      Available strategies = {"LightGBM", "RandomForest", "ExtraTrees",
      "Tree", "Bagging", "AdaBoost" or "Linear"}.
docstr_tok: ["Init","Classifier","object",".","User","can","define","strategy","parameters",".","Parameters","--","--","--","--","--","strategy",":","str",",","default","=","``","LightGBM","''","The","choice","of","the","classifier",".","Available","strategies","=","{","``","LightGBM","''",",","``","RandomForest","''",",","``","ExtraTrees","''",",","``","Tree","''",",","``","Bagging","''",",","``","AdaBoost","''","or","``","Linear","''","}","."]
code: def __init__(self, **params):
      """Init Classifier object.
  
      User can define strategy parameters.
  
      Parameters
      ----------
      strategy : str, default = "LightGBM"
          The choice of the classifier.
          Available strategies = {"LightGBM", "RandomForest", "ExtraTrees",
          "Tree", "Bagging", "AdaBoost" or "Linear"}.
  
      """
      if "strategy" in params:
          self.__strategy = params["strategy"]
      else:
          self.__strategy = "LightGBM"
  
      self.__classif_params = {}
  
      self.__classifier = None
      self.__set_classifier(self.__strategy)
      self.__col = None
  
      self.set_params(**params)
      self.__fitOK = False
  
file_path: MLBox/mlbox/model/classification/classifier.py
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 1 to create a new Classifier object  with example: obj = Classifier()