Question

The main difference between 'supervised' and 'unsupervised' learning is that:

Q: Answer-The main difference between 'supervised' and 'unsupervised' learning is that:

Supervised learning uses labelled training data features target for Classification predict category fraudnot fraud, defaultno default and Regression predict continuous value loan amount, house price. Algorithms of Supervised Learning are LinearLogistic Regression, Decision Trees, SVM, Random Forest, Neural Networks. Unsupervised learning uses data with no labels for Clustering K-Means, DBSCAN customer segmentation, Dimensionality Reduction PCA compressing features and Association Rules Apriori product bundling. In Banking, Supervised learning is used for credit scoring and Unsupervised learning is used for detecting unusual transaction clusters potential fraud rings.

A Supervised learning uses more data; unsupervised learning uses less data

B Supervised learning uses labelled data; unsupervised learning uses unlabelled data

C Supervised learning requires human intervention during every prediction; unsupervised learning is fully automated

D Supervised learning is used only for classification; unsupervised learning is used only for regression

E Supervised learning uses neural networks only; unsupervised learning uses decision trees only

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The main difference between 'supervised' and 'unsupervised' learning is that:

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