code: def test_multi_target(self):
      y_multi = np.random.multinomial(1, (0.3, 0.3, 0.4), self.n)
      rf_model = RandomForestClassifier(
          max_features=0.33, min_samples_leaf=5, n_estimators=5
      )
      rf_plus_model = RandomForestPlusClassifier(rf_model)
      rf_plus_model.fit(self.X, y_multi)
      scores = rf_plus_model.get_mdi_plus_scores(
          self.X, y_multi, scoring_fns=mean_squared_error
      )
  
imports: import copy
  import numpy
  import random
  import scipy
  from sklearn.linear_model import Ridge, LinearRegression
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
  from sklearn.metrics import r2_score, log_loss, roc_auc_score, mean_squared_error
  from imodels.importance.block_transformers import IdentityTransformer, TreeTransformer, CompositeTransformer, MDIPlusDefaultTransformer
  from imodels.importance.ppms import RidgeRegressorPPM, LogisticClassifierPPM, RobustRegressorPPM
  from imodels.importance.mdi_plus import TreeMDIPlus, ForestMDIPlus
  from imodels.importance.rf_plus import RandomForestPlusClassifier
label_desc: Use image node_id 6 for calling the TestMDIPlus obj's underlying member method code with example usage: obj.test_multi_target() without return types