Ensemble learning combines several models into one predictive model to decrease the variance and improve results. The ensemble method is divided into two groups - the sequential method and the parallel method.
Sequential method - base learners are generated sequentially
Parallel method - base learners are generated parallelly
Ensembles techniques are -
- Bagging
- Stacking
- Boosting
Scenario - suppose you want to buy a new pair of headphones. What will you do? Being an aware consumer, first, you will do research on which company offers the best headphones and also take some suggestions from your friends. In short, you will be making informed decisions after thoroughly researching work.