COSC-E4 CS Elective 4 (Machine Learning) Lesson 2: Supervised Learning

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What does supervised learning regression predict?

Continuous values (correct)

Discrete values

Categorical values

Binary values

In supervised learning, what percentage of data is typically used for training?

60%

80% (correct)

90%

40%

What is the main difference between classification and regression in supervised learning?

Classification predicts continuous values, while regression predicts discrete values.

Regression is used for categorical data, while classification is used for numerical data.

Classification focuses on binary outcomes, while regression focuses on multi-class outcomes.

Classification deals with defined labels, while regression deals with continuous values. (correct)

What is the purpose of testing data in supervised learning?

To compare model predictions with actual outputs Signup and view all the answers

In binary classification, what are the typical prediction outcomes?

"Yes" or "No" Signup and view all the answers

What kind of output does regression deal with in supervised learning?

Continuous values Signup and view all the answers

What is the primary purpose of the training set in supervised machine learning?

To adjust the model's weights and minimize prediction error Signup and view all the answers

Which set is used to tune the model's hyperparameters, such as learning rate or regularization parameter?

Validation set Signup and view all the answers

What is the primary purpose of the test set in supervised machine learning?

To estimate the generalization error and evaluate the model's performance on unseen data Signup and view all the answers

Which step in the supervised machine learning process involves normalization and data transformation procedures?

Pre-processing data Signup and view all the answers

What is the purpose of the training and test data split in supervised machine learning?

To decide which strategy to use for evaluation purposes and have a test set to evaluate the model later Signup and view all the answers

Which step in the supervised machine learning process involves trying different model parameters and selecting the best model?

Model tuning and selection Signup and view all the answers

What is the primary goal of supervised learning?

To train a model to make accurate predictions on new, unseen data based on labeled examples Signup and view all the answers

Which of the following is a major advantage of supervised learning?

The classes in the training data directly represent real-world features Signup and view all the answers

What is the first step in the supervised learning process?

Gather labeled training data Signup and view all the answers

Which of the following is a potential disadvantage of supervised learning?

All of the above Signup and view all the answers

What is the purpose of splitting the labeled data into training, validation, and testing sets?

To ensure that the model is evaluated on unseen data Signup and view all the answers

In supervised learning, which of the following is true about the relationship between the input data and output labels?

The model is trained to detect the underlying patterns and relationships between the input data and output labels Signup and view all the answers