Unit 4
Machine Learning
[25.1] Which of the following are approaches for supervised learning? Choose all that apply.
a) Classification
b) Clustering
c) Regression
d) Validation
e) Testing
[25.2] What type of data does a clustering algorithm work with?
a) Labeled data
b) It doesn’t matter
c) Unlabeled data
d) Both labeled and unlabeled data
[25.3] For each scenario, choose the correct combination of learning category and reasoning category.
a) Predicting the likelihood of a person getting a loan approval.
b) Segmenting customers based on purchasing behavior.
c) Estimating the price of a house based on features.
d) Whether a house is likely to be sold within 30 days.
e) Predicting price ranges (high, med, low).
[25.4] Classification is used when the goal is to predict a ________ value.
[25.5] Regression is used to predict a ________ value.
[25.6] True / False: It is common for machine learning to use a single feature to answer a question.
[25.7] What is the goal of clustering?
[25.8] Which of the following is an example of unsupervised learning?
a) Categorizing news articles by topic
b) Predicting the next day's stock price
c) Classifying images of animals
d) Diagnosing diseases from medical images
[25.9] Which of the following is NOT a characteristic of unsupervised learning?
a) It groups data points into clusters.
b) It predicts future outcomes based on labeled data.
c) It uncovers hidden patterns in data without labels.
d) It does not require labeled data.