What are the advantages of supervised learning?

What are the advantages of supervised learning?

Supervised learning offers several advantages, such as high accuracy, ease of implementation, and the ability to learn from labeled data.

Can you explain how it achieves high accuracy?

High accuracy in supervised learning is achieved because the model is trained on labeled data, allowing it to learn the correct output for given inputs.

What types of problems is supervised learning best suited for?

Supervised learning is best suited for classification and regression problems, where the output is known and can be used for training.

Are there any limitations to supervised learning?

Yes, limitations include the need for a large amount of labeled data and the potential for overfitting if the model is too complex.

How does it compare to unsupervised learning?

Unlike supervised learning, unsupervised learning works with unlabeled data, focusing on finding patterns or groupings without predefined outputs.