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Ensemble method is the process by which various models are created and consolidated in order to understand a specific computer intelligence problem. This prompts better prescient performance than could be acquired from any of the constituent learning models alone. Fundamentally, an ensemble is a supervised learning method for joining various weak learners/models to deliver a strong learner. Ensemble model works better, when we group models with low correlation. Figure 1.7 gives the various ensemble methods which are in use. Following are some of the techniques used for ensemble.

Figure 1.7 Ensemble methods.