What is the main advantage of binary encoding over one-hot encoding?

It preserves the ordinal relationship between categories.

It reduces the number of columns needed to represent categories.

It avoids any information loss compared to one-hot encoding.

It uses the target variable to improve predictive power.

What is the primary purpose of t-SNE?

To remove features with low variance

To reduce dimensionality for visualization

To encode categorical variables

CertNexusCertified Data Science Practitioner (CDSP)

Domain 3Objective 3

Objective 3.3 Carry Out Feature Engineering CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 5)

Part of the 3.0 Performing exploratory data analysis domain, which accounts for 25-36% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.

54questions here

11free pages

27concepts

25-36%of the exam

27 Concepts in This Objective

One-hot encoding
Target encoding
Label/Ordinal encoding
Dummy encoding
Effect encoding
Binary encoding
Base-N encoding
Hash encoding
Split features
Text manipulation - Split
Text manipulation - Trim
Text manipulation - Reverse
Manipulate data - Split names
Manipulate data - Extract year from title
Convert dates to useful features
PCA (Principal Component Analysis)
Missing value ratio
t-SNE (t-Distributed Stochastic Neighbor Embedding)
Low-variance filter
Random forest feature importance
High-correlation filter
Backward feature elimination
SVD (Singular Value Decomposition)
Forward feature selection
False discovery rate
Factor analysis
Feature importance methods

Questions 21–25

21foundation · easy
A data scientist notices that a text column contains values with extra spaces at the beginning and end, such as ' apple '. They want to clean this data. Which text manipulation technique should they use?
Select an answer first
22foundation · easy
A data scientist has a categorical feature 'color' with values 'red', 'green', and 'blue'. They want to convert this feature for use in a model without implying any order among the colors. Which encoding method should they use?
Select an answer first
23foundation · medium
A data science team is building a customer segmentation model with 80 candidate features. They want to reduce the feature set by starting with an empty set and, at each iteration, adding the feature that most improves model performance. Which feature selection technique does this describe?
Select an answer first
24foundation · easy
What is the main advantage of binary encoding over one-hot encoding?
Select an answer first
25foundation · easy
What is the primary purpose of t-SNE?
Select an answer first

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Objective 3.3 Carry Out Feature Engineering CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 5)

Questions 21–25

A data scientist notices that a text column contains values with extra spaces at the beginning and end, such as ' apple '. They want to clean this data. Which text manipulation technique should they use?

A data scientist has a categorical feature 'color' with values 'red', 'green', and 'blue'. They want to convert this feature for use in a model without implying any order among the colors. Which encoding method should they use?

A data science team is building a customer segmentation model with 80 candidate features. They want to reduce the feature set by starting with an empty set and, at each iteration, adding the feature that most improves model performance. Which feature selection technique does this describe?

What is the main advantage of binary encoding over one-hot encoding?

What is the primary purpose of t-SNE?

Keep studying — 3.0 Performing exploratory data analysis