7 previous exams from Business Analytics and Decision Support (1BK40) from 2015 till 2018. This course used the book Data Science for Business (ISBN: 9781449361327). The newest exam of November 2018 is included as well. The solutions are provided as well.
Machine Learning (Data Mining) - Samenvatting (slides en handboek)
Full Summary of Chapters and Lecture Slides Data Science for Business
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1BK40 (1BK40)
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Student name:
Student number:
Examination cover sheet
(to be completed by the examiner)
Course name: Business Analytics & Decision Support Course code: 1BK40
Date: 05-11-2015
Start time: 13:30 End time : 16:30
Number of pages: 15 (excl. this cover sheet)
Number of questions: 5
Maximum number of points/distribution of points over questions:100
Method of determining final grade: The exam grade is determined by dividing the total points by
10. The exam grade determines 50% of the final grade for the course.
Answering style: Open questions
Exam inspection: With your instructor
Other remarks: All questions to this exam must be answered on the exam itself, in the white space
immediately following the question. Write now your name and student ID on each sheet of the exam.
You must hand in the exam question sheets together with your answers.
Make sure your answers are brief and to the point.
Good luck!!!
Instructions for students and invigilators
Permitted examination aids (to be supplied by students):
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X Calculator
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⇤ Graphic calculator
⇤ Lecture notes/book
⇤ One A4 sheet of annotations
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⇤ Other:
Important: During written examinations, the following actions will in any case be
• examinees are only permitted to visit the toilets under supervision deemed to constitute fraud or attempted fraud:
• it is not permitted to leave the examination room within 15 minutes • using another person’s proof of identity/campus card (student iden-
of the start and within the final 15 minutes of the examination, tity card)
unless stated otherwise • having a mobile telephone or any other type of media-carrying de-
• examination scripts (fully completed examination paper, stating vice on your desk or in your clothes
name, student number, etc.) must always be handed in • using, or attempting to use, unauthorized resources and aids, such
• the house rules must be observed during the examination as the internet, a mobile telephone, etc.
• the instructions of examiners and invigilators must be followed • using a clicker that does not belong to you
• no pencil cases are permitted on desks • having any paper at hand other than that provided by TU/e, unless
• examinees are not permitted to share examination aids or lend them stated otherwise
to each other • visiting the toilet (or going outside) without permission or super-
vision
Associated with the Central Examination Regulations
, EINDHOVEN UNIVERSITY OF TECHNOLOGY
Department of Industrial Engineering and Innovation Sciences
Business Analytics & Decision Support (1BK40)
Thursday, November 5, 2015, 13h30 – 16h30.
Your answers should be formulated and written down clearly, on the exam itself, in
the white space immediately following the question. Make sure your answer is brief
and to the point.
Question 1 (20 points)
1.1. Fuzzy sets are used to represent the concept of gradualness. Provide two dif-
ferent examples of situations where it is useful to account for this gradualness.
1.2. For each of the questions below, what is the data-mining task or other technique
that is most suitable to be used in answering the question?
(a) Who are the most profitable customers?
(b) Is there really a difference between the profitable customers and the aver-
age customer?
1
, (c) How much revenue should I expect this customer to generate?
(d) Do customers form natural groups or segments?
1.3. Consider the following fitting graph, where each point on a curve represents
the error rate of a model with a specified complexity (as indicated on the
horizontal axis). Indicate (highlight) on the graph which complexity level you
would choose for your model and elaborate on the reasons.
2
, 1.4. Consider a simple two-class problem with classes c1 and c2 , and attributes x
and y. Attribute x has two values, p and q, and y has two values, r and s. You
are provided with the following small training set of examples:
Instance x y Class
1 p r c1
2 p r c1
3 p r c1
4 q s c1
5 p s c2
6 q r c2
7 q s c2
8 q r c2
The marketing team requires your assistance in evaluating a model XPTO with
a total accuracy of 75%. This model predicts 75% of the customers that will
be in class c2 correctly. Write down the confusion matrix for model XPTO.
3
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