Machine Learning Quizzes for Year 13 Computer Science Students

Question 1

What is the primary objective of regression in machine learning?

Accepted Answer

Predicting continuous numerical values

Answer

Classifying data into discrete categories

Answer

Discovering hidden patterns and structures in data

Answer

Clustering data points based on their similarities

Question 2

Which of the following is NOT a common application of machine learning in healthcare?

Accepted Answer

Managing financial investments

Answer

Diagnosing diseases based on medical images

Answer

Identifying patterns in electronic health records

Answer

Predicting the risk of developing chronic conditions

Question 3

What is the primary purpose of cross-validation in machine learning?

Accepted Answer

Evaluating the performance and robustness of a model

Answer

Adjusting model parameters to optimize accuracy

Answer

Reducing the computational cost of training a model

Answer

Selecting the most informative features for a model

Question 4

Which of the following algorithms is widely used for clustering data?

Accepted Answer

K-means

Answer

Linear regression

Answer

Decision tree

Answer

Support vector machine

Question 5

What is the primary role of regularization in machine learning?

Accepted Answer

Preventing overfitting by penalizing model complexity

Answer

Improving model accuracy by increasing model parameters

Answer

Reducing the computational cost of training a model

Answer

Identifying the most important features in a dataset

Question 6

What is the primary goal of feature engineering in machine learning?

Accepted Answer

Transforming raw data into features that are more suitable for modeling

Answer

Reducing the number of features in a dataset

Answer

Improving model accuracy

Answer

Reducing the computational cost of training a model

Question 7

What is the key difference between supervised and unsupervised learning?

Accepted Answer

Supervised learning uses labeled data while unsupervised learning uses unlabeled data

Answer

Supervised learning is used for classification while unsupervised learning is used for regression

Answer

Unsupervised learning is more complex than supervised learning

Answer

There is no difference between supervised and unsupervised learning

Question 8

Which of the following is an example of a regression task in machine learning?

Accepted Answer

Predicting house prices

Answer

Classifying images

Answer

Clustering customer data

Answer

Detecting fraud

Question 9

What is the role of bias-variance trade-off in machine learning?

Accepted Answer

To balance the complexity and generalizability of a model

Answer

To select the best features for the model

Answer

To prevent overfitting

Answer

To visualize the model's predictions

Question 10

What is the goal of unsupervised clustering in machine learning?

Accepted Answer

To group similar data points together

Answer

To predict the value of a target variable

Answer

To classify data points into different categories

Answer

To visualize the data in a meaningful way

Question 11

What is the purpose of feature scaling in machine learning?

Accepted Answer

To improve the convergence of learning algorithms

Answer

To reduce the dimensionality of data

Answer

To enhance the interpretability of models

Answer

To detect outliers in data

Question 12

Which of the following is a primary goal of machine learning?

Accepted Answer

To create models that can generalize well to new data

Answer

To make machines that think like humans

Answer

To automate repetitive tasks

Answer

To replace human workers

Question 13

Which of the following is NOT a benefit of using machine learning?

Accepted Answer

Elimination of the need for human involvement

Answer

Improved decision making

Answer

Increased efficiency and productivity

Answer

Reduced human error

Question 14

Which of the following is an unsupervised learning technique commonly employed for dimensionality reduction?

Accepted Answer

Principal component analysis

Answer

Clustering

Answer

Factor analysis

Answer

Linear discriminant analysis

Question 15

In which industry is machine learning extensively used for fraud detection?

Accepted Answer

Finance

Answer

Healthcare

Answer

Retail

Answer

Education

Question 16

In a regression analysis, the dependent variable is the:

Accepted Answer

Target attribute

Answer

Input features

Answer

Predicted value

Answer

Weights

Question 17

Which of these algorithms is primarily used for classification tasks?

Accepted Answer

Logistic regression

Answer

Linear regression

Answer

K-means clustering

Answer

Principal component analysis

Question 18

Which of these metrics is used to evaluate the performance of a regression model?

Accepted Answer

Mean squared error

Answer

Accuracy

Answer

Precision

Answer

F1 score

Question 19

What is the primary distinction between supervised and unsupervised learning?

Accepted Answer

Supervised learning uses labeled data, while unsupervised learning does not.

Answer

Supervised learning is used for classification tasks, while unsupervised learning is used for regression tasks.

Answer

Supervised learning is more accurate than unsupervised learning.

Answer

Supervised learning is more computationally expensive than unsupervised learning.

Question 20

What is the potential impact of bias in machine learning?

Accepted Answer

Bias can lead to unfair or inaccurate predictions.

Answer

Bias can improve model performance by reducing variance.

Answer

Bias is always a negative factor in machine learning.

Answer

Bias can only be introduced through the training data.

Question 21

Revised: The primary aim of supervised machine learning algorithms is to:

Accepted Answer

Predict or classify new data based on labeled training data

Answer

Identify patterns without any external guidance

Answer

Reduce features through dimensionality reduction

Answer

Generate new data similar to the original set

Question 22

Revised: Linear regression falls under which category of machine learning algorithms?

Accepted Answer

Regression

Answer

Classification

Answer

Clustering

Answer

Dimensionality reduction

Question 23

Revised: A key advantage of using decision trees for classification tasks is its:

Accepted Answer

High interpretability and handling of diverse data types

Answer

High accuracy and low computational cost

Answer

Robustness to noise and outliers

Answer

Efficient handling of large datasets

Question 24

Revised: The primary purpose of cross-validation in machine learning is to:

Accepted Answer

Reduce overfitting and enhance generalization

Answer

Evaluate model performance on unseen data

Answer

Tune hyperparameters and select the best model

Answer

Visualize the decision boundaries of a model

Question 25

Revised: Which of the following is not an example of an unsupervised machine learning algorithm?

Accepted Answer

Logistic regression

Answer

K-Means clustering

Answer

Principal component analysis

Answer

Hierarchical clustering

Question 26

Revised: In machine learning, the distinction between a feature and a label is:

Accepted Answer

A feature is an input, while a label is an output

Answer

A feature is numerical, while a label is categorical

Answer

A feature is used for training, while a label is used for testing

Answer

A feature is independent, while a label is dependent

Question 27

Which of the following types of machine learning involves training a model on labeled data, such as a dataset with known outcomes?

Accepted Answer

Supervised learning

Answer

Transfer learning

Answer

Unsupervised learning

Answer

Reinforcement learning

Question 28

In machine learning, what is the primary goal of regression?

Accepted Answer

Predicting a continuous value outcome

Answer

Detecting patterns and relationships in data

Answer

Reducing the dimensionality of data

Answer

Classifying data into discrete categories

Question 29

In machine learning, what is the fundamental difference between supervised and unsupervised learning?

Accepted Answer

Supervised learning uses labeled data while unsupervised learning uses unlabeled data

Answer

Supervised learning models predict continuous values while unsupervised learning models predict categorical values

Answer

Unsupervised learning models are trained on larger datasets than supervised learning models

Answer

Supervised learning algorithms are more complex than unsupervised learning algorithms

Question 30

What is the role of cross-validation in evaluating machine learning models?

Accepted Answer

Estimating the model's performance on unseen data and reducing overfitting

Answer

Selecting the best machine learning algorithm

Answer

Improving the model's accuracy

Answer

Determining the optimal hyperparameters

Question 31

What is the main purpose of preprocessing data in machine learning?

Accepted Answer

Improving data quality and preparing it for modeling

Answer

Reducing the size of the dataset

Answer

Converting the data into a different format

Answer

Visualizing the data more effectively

Question 32

What is the importance of feature engineering in machine learning?

Accepted Answer

Creating more informative and relevant features for model training

Answer

Reducing the number of features in the dataset

Answer

Improving the visual presentation of the data

Answer

Automating the feature selection process

Question 33

What is the primary objective of supervised learning?

Accepted Answer

To construct a mapping between input data and output labels.

Answer

To learn by interacting with an environment and receiving rewards or punishments.

Answer

To identify patterns and structures within data without labeled examples.

Question 34

Which of the following algorithms is commonly used in supervised learning?

Accepted Answer

Decision tree

Answer

Autoencoder

Answer

Principal component analysis

Answer

K-means clustering

Question 35

What is the key distinction between classification and regression tasks in machine learning?

Accepted Answer

Classification involves predicting discrete categories, while regression involves predicting continuous values.

Answer

Classification utilizes supervised learning, whereas regression employs unsupervised learning.

Question 36

What is the role of the validation set in machine learning?

Accepted Answer

To evaluate the effectiveness of a model on unseen data before deploying it.

Answer

To gather training data for the model.

Answer

To store the best-performing model for future use.

Question 37

Which of the following metrics is primarily used to assess the performance of classification models?

Accepted Answer

Accuracy

Answer

Mean squared error

Answer

Adjusted R-squared

Question 38

What is the primary purpose of feature engineering in machine learning?

Accepted Answer

To transform raw data into features that are more suitable for machine learning algorithms.

Answer

To identify the most important features from a dataset.

Answer

To reduce the dimensionality of a dataset.