APPLICATION OF SUPERVISED LEARNING
ARTIFICIAL INTELLIGENCE
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Supervised learning
|
|
|
Semi-supervised learning
|
|
|
Unsupervised learning
|
|
|
Reinforcement learning
|
Detailed explanation-1: -In a nutshell, semi-supervised learning (SSL) is a machine learning technique that uses a small portion of labeled data and lots of unlabeled data to train a predictive model.
Detailed explanation-2: -Semi-supervised learning is a hybrid of supervised and unsupervised machine learning. The Semi-supervised learning used for the same purposes as supervised learning, where it employs both labelled and unlabeled data for training typically a small amount of labelled data with a significant amount of unlabeled data.
Detailed explanation-3: -Labeled data is used in supervised learning, whereas unlabeled data is used in unsupervised learning . Labeled data is more difficult to acquire and store (i.e. time consuming and expensive), whereas unlabeled data is easier to acquire and store.