Hello All,
I am new to Machine Learning Algorithms. I was trying to perform stacking on UNSW-NB15 dataset using Light Gradient Boosted Machine (LGBM) and K nearest neighbor as base classifiers and random forest as meta classifier. But, the accuracy of stacking is not improved than accuracy of LGBM. The accuracy I am getting with LGBM, the same accuracy I am getting from stacking. Your comments will help me a lot. Thanks in advance. Here is my code segment:
rf = RandomForestClassifier(n_estimators = 100, n_jobs = -1,random_state =50,max_features = “auto”, min_samples_leaf = 50)
classifiers = [lgbm,knn]
stacking = StackingClassifier(classifiers, meta_classifier = rf)
stacking.fit(x_train, y_train)