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C. Competency-based/Application-based questions: #Problem Solving & Logical Reasoning
1. The diagrams used in KNN algorithm and K-means are very similar. An employee in Teeksha Global Tech was facing
high ambiguity, as to when we should use either of these as both of these lead to classification. Could you guide her
with some examples, which algorithm to use and when?
2. In a futuristic city, the SmartCommute (City bus service) optimizes bus routes, adjusting to new routes based on traffic
conditions from real-time feedback. One day, a sudden storm caused traffic chaos, but the system quickly adapted and
maintained efficient service. Name the type of Machine Learning used by it.
Assertion and reasoning questions:
Direction: Questions 3-4, consist of two statements – Assertion (A) and Reasoning (R). Answer these questions 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.
3. Assertion(A): Causation states that any change in the value of one variable will definitely cause a change in the value
of the second variable.
Reasoning(R): The correlation is a statistical method that indicates whether a pair of variables has a quadratic
relationship with each other.
4. Assertion(A): Linear Regression method finds the most accurate straight line that best describes the relationship
between the dependent and the independent variables, with minimum error.
Reasoning(R): Linear Regression has its limitations, but its simplicity, interpretability, and efficiency often exceed these
limitations.
Direction: Questions 5-6 below, consist of two statements
Two statements are given . Statement 1 and Statement 2 . Examine the statements and answer the question according
to the instruction given below.
a. Statement 1 is TRUE , Statement 2 is TRUE
b. Statement 1 is FALSE , Statement 2 is FALSE
c. Statement 1 is TRUE , Statement 2 is FALSE
d. Statement 1 is FALSE , Statement 2 is TRUE
5. Statement 1: It is inefficient to train the machine on Linear Regression model.
Statement 2: Linear Regression Model is quite prone to overfitting.
6. Statement 1: Clustering is an unsupervised machine learning technique that automatically divides the data into clusters
or groups of similar elements.
Statement 2: The biggest advantage of the K-means algorithm is that it can cluster large data sets quite efficiently.
In Life #Interdisciplinary
Have you heard about DNA Sequence Classification? Find out about this topic and present your findings in
class.
Machine Learning Algorithms 363

