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Case Study 3: An autonomous vehicle is learning to navigate through a city environment. It receives feedback in the
form of rewards for reaching its destination safely and penalties for traffic violations. Which type of learning is this case
study most likely based on?
Case Study 4: A healthcare provider wants to identify patterns in patient data to personalize treatment plans. They
have a dataset with various patient attributes but no predefined labels indicating specific treatment plans. Which type
of learning is this case study most likely based on?
Case Study 5: A manufacturing company wants to optimize its production process by detecting anomalies in sensor
data from machinery. They have a dataset with examples of normal and anomalous behaviour. Which type of learning
is this case study most likely based on?
4. Identify the type of model (classification, regression, clustering, association model) are the following case studies most
likely based on?
a. A bank wants to predict whether a loan applicant will "default" or "non-default" on their loan payments. They have
a dataset containing information such as income, credit score, loan amount, and employment status.
b. A real estate agency wants to predict the selling price of houses based on various features such as size, location,
number of bedrooms, and bathrooms. They have a dataset containing historical sales data.
c. A marketing company wants to segment its customer base into distinct groups based on purchasing behaviour for
targeted marketing campaigns. They have a dataset containing information such as purchase history, frequency of
purchases, and amount spent.
d. A grocery store wants to identify associations between different products purchased by customers to understand
which products are commonly bought together. They have a transaction dataset containing records of items
purchased together during each transaction.
5. Convert the following scenarios to perceptron:
a. A healthcare provider wants to improve patient care by predicting the length of hospital stays for different medical
conditions. They have a dataset containing patient demographics, medical history, and treatment details. The task
involves:
(i) To predict whether a patient will have a short or long hospital stay.
(ii) To predict the number of days a patient will stay in the hospital.
(iii) To segment patients into groups with similar characteristics for personalized treatment plans.
(iv) To identify patterns in patient treatments and outcomes.
(v) Identify the type of model (classification, regression, clustering, and association model) in the above tasks.
b. Context: A homeowner is deciding whether to invest in solar panels for their house.
Factors: - Do I have a sufficient average amount of sunlight in my area?
Are there any available incentives or rebates for installing solar panels?
• Does installing solar panels impact the value of my home?
• Does solar energy lead to environmental benefits? value of my home?
• Does solar energy lead to environmental benefits?
Assertion and Reasoning Questions:
Direction: Questions 6-7, consist of two statements – Assertion (A) and Reasoning (R). Answer these questions by
selecting the appropriate option given below:
a. Both A and R are true and R is the correct explanation of A.
b. Both A and R are true but R is not the correct explanation of A.
c. A is true but R is false.
d. A is false but R is true.
Advanced Concepts of Modeling in AI 215

