Removing info about new weaklearner

src/mlpack/methods/adaboost/adaboost_impl.hpp

@@ -120,8 +120,6 @@ double AdaBoost<WeakLearnerType, MatType>::Train(
     weights = arma::sum(D);
 
     // Use the existing weak learner to train a new one with new weights.
-    // In fact, the new weak learner just inherits some hyperparameters
-    // from existing weak learner.
     WeakLearnerType w(other, tempData, labels, numClasses, weights);
     w.Classify(tempData, predictedLabels);
 

src/mlpack/methods/decision_tree/decision_tree_impl.hpp

@@ -88,11 +88,10 @@ DecisionTree<FitnessFunction,
 
   // Set the correct dimensionality for the dimension selector.
   dimensionSelector.Dimensions() = tmpData.n_rows;
-  arma::Row<size_t> passlabels = tmpLabels;
 
   // Pass off work to the Train() method.
   arma::rowvec weights; // Fake weights, not used.
-  Train<false>(tmpData, 0, tmpData.n_cols, passlabels, numClasses, weights,
+  Train<false>(tmpData, 0, tmpData.n_cols, tmpLabels, numClasses, weights,
       minimumLeafSize, minimumGainSplit, maximumDepth, dimensionSelector);
 }