docstr: Fit a propensity model.
  
  Args:
      X (numpy.ndarray): a feature matrix
      y (numpy.ndarray): a binary target vector
docstr_tok: ["Fit","a","propensity","model",".","Args",":","X","(","numpy.ndarray",")",":","a","feature","matrix","y","(","numpy.ndarray",")",":","a","binary","target","vector"]
code: def fit(self, X, y):
      """
      Fit a propensity model.
  
      Args:
          X (numpy.ndarray): a feature matrix
          y (numpy.ndarray): a binary target vector
      """
      self.model.fit(X, y)
  
imports: from abc import ABCMeta, abstractmethod
  import logging
  import numpy
  from pygam import LogisticGAM, s
  from sklearn.metrics import roc_auc_score
  from sklearn.linear_model import LogisticRegressionCV
  from sklearn.model_selection import StratifiedKFold, train_test_split
  import xgboost
label_desc: Use image node_id 4 for calling the PropensityModel obj's underlying member method code with example usage: obj.fit(X, y) without return types