Question

Briefly describe 3 approaches that may be used to identify object classes?

Answer 1

Supervised learning, unsupervised learning, and semi-supervised learning are three approaches that can be used to identify object classes.

Step-by-step explanation:

The three approaches that may be used to identify object classes are:

1. Supervised Learning: In this approach, a labeled dataset is used to train a model that can classify objects into predefined classes. The model learns from the input data and the corresponding labels, and then it can make predictions on new, unseen data.
2. Unsupervised Learning: In unsupervised learning, the algorithm does not have access to labeled data. Instead, it analyzes the input data to find patterns, clusters, or structures. These patterns can be used to identify object classes, even if there are no predefined labels.
3. Semi-supervised Learning: This approach combines supervised and unsupervised learning. It uses a small amount of labeled data and a large amount of unlabeled data. The model is trained on the labeled data and then leverages the unlabeled data to improve its predictions and identify object classes.