Podcast
Questions and Answers
What is the main difference between supervised learning and unsupervised learning?
What is the main difference between supervised learning and unsupervised learning?
- Supervised learning is used for clustering, while unsupervised learning is used for classification
- Supervised learning aims to establish the existence of classes or clusters in the data, while unsupervised learning classifies new data based on the training set
- Supervised learning is used for establishing classes, while unsupervised learning uses class labels in the training data
- Supervised learning uses labeled training data, while unsupervised learning uses unlabeled training data (correct)
What is the primary purpose of supervised learning?
What is the primary purpose of supervised learning?
- To classify new data based on the training set (correct)
- To establish the existence of classes or clusters in the data
- To determine the unknown class labels of training data
- To use unlabeled training data for classification
What is the key objective of unsupervised learning?
What is the key objective of unsupervised learning?
- To classify new data based on the training set
- To establish the existence of classes or clusters in the data (correct)
- To determine the unknown class labels of training data
- To use labeled training data for classification
Flashcards
Supervised Learning
Supervised Learning
Uses labeled data to train a model to classify new data.
Unsupervised Learning
Unsupervised Learning
Uses unlabeled data to find patterns or clusters.
Supervised Learning Purpose
Supervised Learning Purpose
To classify new data based on labeled examples from a training set.
Unsupervised Learning Goal
Unsupervised Learning Goal
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Study Notes
Supervised Learning vs Unsupervised Learning
- Supervised learning involves training a model on labeled data, where the target output is already known, to make predictions on new, unseen data.
- Unsupervised learning involves training a model on unlabeled data, to discover patterns or structure in the data.
Primary Purpose of Supervised Learning
- The primary purpose of supervised learning is to make accurate predictions on new data by learning a mapping between input data and output labels.
Key Objective of Unsupervised Learning
- The key objective of unsupervised learning is to identify patterns, relationships, or anomalies in the data without prior knowledge of the output labels.
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