MACHINE LEARNING

Detailed explanation-1: -True or False: Ensemble learning can only be applied to supervised learning methods. Generally, we use ensemble technique for supervised learning algorithms. But, you can use an ensemble for unsupervised learning algorithms also.

Detailed explanation-2: -Our method provides the diversity which is much needed by the ensemble through semi-supervised learning, while the ensemble provides the semi-supervised part with robustness, as well as facilitating the early-stopping mechanism.

Detailed explanation-3: -Ensemble learning is a general meta approach to machine learning that seeks better predictive performance by combining the predictions from multiple models.

Detailed explanation-4: -Ensemble learning is the process by which multiple models, such as classifiers or experts, are strategically generated and combined to solve a particular computational intelligence problem. Ensemble learning is primarily used to improve the (classification, prediction, function approximation, etc.)