Sr. No.

Question Option 1
1 What is the purpose of feature selection in feature engineering?
A) To add more features to the dataset.
2Which of the following is a common method to handle missing data A) in
Deleting
a dataset?
the entire dataset.
3 What is the effect of creating polynomial featuresA) in Ita reduces
dataset?the dimensionality of the data.
Which4of the following techniques is used for dimensionality reduction in feature A) engineering?
Decision tree.
5 Why is feature transformation used in feature engineering?
A) To increase the size of the dataset.
6 Which of the following methods can be used to detect outliers inA) a dataset?
Min-max normalization.
7 Which of the following is NOT a benefit of feature engineering?A) Improving model accuracy
8 Which of the following is a challenge associated with multiscale
A) Managing analysis?
the increased complexity and computational demand
9 What is the main goal of data preprocessing
A) To in machine
improve thelearning?
quality and suitability of data for model trainin
10 Why is it important to handle outliersA)
during
Outliers
preprocessing?
can distort statistical analyses and model performanc
 Option 2 Option 3 Option 4 Option 5
he number of featuresC) byTo selecting
transform D) relevant
thefeatures
most Tointo
increase the dimensionality
a different
ones. format. of the feature space.
ng missing values with the mean, C) median,
Ignoring
D) or
Generating
themode.
missingsynthetic
data. data to replace the missing values.
el complexity by addingC) It
interaction
simplifiesterms
the model
andD)higher-order
by reducingnumerical
It converts overfitting.
features. data into categorical data.
B) Logistic regression.
C) Principal component analysisD) (PCA).
K-means clustering.
hematical operations to existing
C) Tofeatures,
reduce the D) To
creating
number simplify
new
of ones. the dataset by removing noise.
features.
B) Z-score. C) Cross-validation. D) Random search.
B) Reducing the complexityC) Making
of the themodel
model moreD) interpretable
Increasing the size of the dataset
B) Simplifying feature
C) Reducing
engineering. D) Handling
the dimensionality missing values in a dataset.
of features.
B) To increase the sizeC) of
Tothe
select
dataset.
the best model D)for
Toprediction.
perform hyperparameter tuning.
B) To ensure all dataC)points
To reduce
are numerical.
the number of features
D) To increase
in the dataset.
the size of the dataset.
Option 6 Option 7 Option 8 Correct answer(1,2,3,4,5,6,7,8)
2
2
2
3
2
2
3
1
1
1
Question type Time(in seconds)
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Objective 60
Out of marks Explanation
1
1
1
1
1
1
1
1
1
1
Character Limit Shuffle Answer Options
YES
YES
YES
YES
YES
YES
YES
YES
YES
YES
Is Multiple Choice CO Mapping
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
Blooms Mapping Reference