code: def predict(self, X):
      n = X.shape[0]
      pred = np.zeros(n)
      for i in range(n):
          exp = self.explain(X[i, :])
          pred[i] = exp["pred"][0]
      return pred
  
imports: import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  from .._explainer import Explainer
  import numpy
  from sklearn.ensemble import GradientBoostingRegressor, RandomForestRegressor
  from sklearn.linear_model import Ridge
  from sklearn.metrics import mean_squared_error
label_desc: Use image node_id 4 for calling the MAPLE obj's underlying member method code with example usage: obj.predict(X) and returns: pred