
Data Science 2
Authored by Prema Kadam
Other
University
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32 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Saisha and Akhil are on a quest to find the distance between two magical points in their enchanted forest, represented by the tuples (3, 5) and (2, 0). Can you help them calculate the Euclidean distance between these two objects?
5.1
5
6
none of them
2.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Hey there, math wizards! Vanya and Aanya are on a quest to find the Supremum distance between two magical objects represented by the tuples (3, 5) and (2, 0). Can you help them uncover the mystery of the distance? What do you think it is?
5
5.1
6
none of the above
3.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Hey there, math whizzes! Aanya, Saisha, and Prisha are having a debate about distances in geometry. They stumbled upon a term that describes the straight-line distance between two points in Euclidean space. Can you help them fill in the blank? Euclidean distance is also known as ______________
L-1 Norm
L-2 Norm
L-3 Norm
None of the above
4.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Hey there, math whizzes! Advait and Aditi are having a friendly competition to see who can calculate the cosine similarity between two document vectors. They have d1 = (4, 0, 3) and d2 = (3, 0, 4). Can you help them find out how similar these vectors are?
1
0
0.96
0.5
5.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Hey there, Vanya! Let's put your knowledge to the test. Which of the following is an essential process where intelligent methods are used to uncover hidden data patterns? Think carefully!
Warehousing
Data Mining
Text Mining
Data Selection
6.
MULTIPLE CHOICE QUESTION
30 sec โข 1 pt
Hey Riyaan! In the world of data analysis, there's a fun term that describes the process of identifying those unusual data points that stand out from the rest. What is this exciting process called?
bjective measures
taxonomy formation
anomaly mining
subjective measures
7.
MULTIPLE SELECT QUESTION
45 sec โข 1 pt
Hey there, data enthusiasts! Can you help Avani figure out what type of clustering algorithm K-Means is? Is it a magical method of grouping data points based on their distances, or does it partition them like a pro? Let's find out!
Distance based
Partition based
Density based
Hierarchical
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