MCQs

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Overall MCQs for Reference

What does cardinality refer to in the context of machine learning data?
a. The average value in a column
b. The number of unique values in a column
c. The number of columns in data
d. The variance of a column
Answer: b. The number of unique values in a columndatacamp
Which feature type is most likely to have high cardinality?
a. Binary flag
b. Country code
c. Unique user ID
d. Gender
Answer: c. Unique user IDkgptalkie+1
What is an example of low cardinality categorical variable?
a. Social security number
b. Order ID
c. Gender
d. Email address
Answer: c. Genderkgptalkie
Why is high cardinality problematic in one-hot encoding?
a. It increases bias
b. It reduces memory usage
c. It increases feature space exponentially
d. It improves accuracy
Answer: c. It increases feature space exponentiallytowardsdatascience
How can high cardinality affect model performance?
a. Leads to underfitting
b. Might cause curse of dimensionality
c. Reduces variance
d. Only impacts regularization
Answer: b. Might cause curse of dimensionalitytowardsdatascience
Which of the following describes a one-to-many relationship?
a. One value relates to only one other
b. One value relates to many values
c. Many values relate to one
d. Values are unrelated
Answer: b. One value relates to many valuesindeed+1
Which relationship has the minimum possible cardinality for participation?
a. Zero
b. One
c. Two
d. Many
Answer: a. Zeroexamveda
The cardinality of a set with n elements is:
a. n^2
b. n!
c. n
d. 2n
Answer: c. ngeeksforgeeks
What is the cardinality of the power set of a set with n elements?
a. n
b. n!
c. 2^n
d. n^n
Answer: c. 2^ngeeksforgeeks
In an entity-relationship diagram, what does cardinality define?
a. Table size
b. Number of relationships
c. Number of entities linked
d. Relationship constraints
Answer: d. Relationship constraintswikipedia
Which of the following would be an example of a column with high cardinality?
a. Gender
b. Product category
c. User email
d. Continent
Answer: c. User emaildatacamp
Reducing the number of distinct values in a feature is called:
a. Binning
b. Normalization
c. Encoding
d. Aggregation
Answer: a. Binningtowardsdatascience
What is a common solution for high-cardinality categorical features?
a. Drop the feature
b. Integer encoding
c. Group rare categories
d. Normalize values
Answer: c. Group rare categoriestowardsdatascience
Which type of relationship cardinality is rarest in relational databases?
a. One-to-one
b. One-to-many
c. Many-to-many
d. None
Answer: a. One-to-onecoursera+1
High cardinality is most problematic for which technique?
a. Mean imputation
b. Scaling
c. One-hot encoding
d. PCA
Answer: c. One-hot encodingtowardsdatascience
The number of tuples in a relation is called its:
a. Degree
b. Cardinality
c. Order
d. Domain
Answer: b. Cardinalitytestbook+1
Which column is likely low cardinality in the Titanic dataset?
a. Cabin
b. Name
c. Embarked
d. Ticket
Answer: c. Embarkedkgptalkie
What does ‘many-to-many’ cardinality mean?
a. One entity relates to many others; others to one
b. Each entity relates to multiple others and vice versa
c. Entities are unrelated
d. One entity relates to one other
Answer: b. Each entity relates to multiple others and vice versaindeed+1
High-cardinality features can cause issues in machine learning because:
a. They reduce diversity
b. Models may overfit
c. They lower recall
d. They are always numerical
Answer: b. Models may overfitdatacamp+1
What is ‘low cardinality’?
a. Many categories, few instances
b. Few distinct values, many repeats
c. Many distinct values, many repeats
d. Data not used
Answer: b. Few distinct values, many repeatssolarwinds
Which encoding is preferred for high-cardinality variables?
a. One-hot encoding
b. Frequency encoding
c. Label encoding
d. Standardization
Answer: b. Frequency encodingtowardsdatascience
Which of the following is true about cardinality?
a. It applies only to numerical variables
b. It indicates unique values in a set
c. It is another word for variance
d. It is only used in SQL
Answer: b. It indicates unique values in a setcausalwizard+1
The cardinality of a dataset’s column indicates:
a. The number of records in the dataset
b. The number of duplicate entries
c. The number of unique values
d. The number of missing values
Answer: c. The number of unique valuescausalwizard+1
Which database relationship is the most common?
a. One-to-one
b. One-to-many
c. Many-to-many
d. None
Answer: b. One-to-manycoursera+1
Which statement is true about reducing feature cardinality?
a. It always reduces model performance
b. It can help generalization
c. It never affects overfitting
d. It is only for continuous data
Answer: b. It can help generalizationdatacamp+1
The minimum number of entity instances participating in a relationship is called:
a. Totality
b. Minimum cardinality
c. Maximum cardinality
d. Relationship degree
Answer: b. Minimum cardinalityexamveda
If a variable has unique values for every row, it has:
a. Medium cardinality
b. Low cardinality
c. High cardinality
d. Average cardinality
Answer: c. High cardinalitysolarwinds+1
Which is not an applicable term for cardinality in databases?
a. Degree
b. Tuple count
c. Number of unique values
d. Frequency
Answer: d. Frequencystudyglance+1
A categorical variable with four possible values has cardinality:
a. 1
b. 2
c. 4
d. 8
Answer: c. 4causalwizard
If a variable ‘zip code’ appears with thousands of unique values, its cardinality is:
a. Low
b. High
c. Moderate
d. Zero
Answer: b. Highhoneycomb+1
What is an effect of excessive high-cardinality variables in a model?
a. Simpler models
b. Increased chance of multicollinearity
c. No effect
d. Fewer parameters
Answer: b. Increased chance of multicollinearitytowardsdatascience
The act of combining infrequent levels of a categorical variable to reduce cardinality is known as:
a. Mode imputation
b. Aggregation
c. Binning
d. Grouping rare categories
Answer: d. Grouping rare categoriestowardsdatascience
Which relationship cardinality is visually represented by a crow’s foot at one end in an ER diagram?
a. One-to-one
b. One-to-many
c. Many-to-one
d. None
Answer: b. One-to-manyindeed
Which is not a type of relationship cardinality in data modeling?
a. One-to-one
b. One-to-many
c. Many-to-many
d. None-to-many
Answer: d. None-to-manywikipedia+1
Cardinality does not affect which of the following?
a. Feature selection process
b. Computational resources
c. Number of output classes
d. Missing value imputation
Answer: d. Missing value imputationdatacamp+1
For which dataset feature is reduction of cardinality unhelpful?
a. Unique transaction IDs
b. Country
c. Product category
d. Gender
Answer: a. Unique transaction IDskgptalkie+1
When preparing train/test sets, why might cardinality be an issue?
a. It creates data leakage
b. Rare values might not appear in both sets
c. It increases accuracy
d. It makes splitting faster
Answer: b. Rare values might not appear in both setskgptalkie+1
What is cardinality in power sets with n elements?
a. n
b. n!
c. 2^n
d. n^n
Answer: c. 2^ngeeksforgeeks
What does “unique” cardinality mean for a variable?
a. Every value is identical
b. Every value is missing
c. Every value is different
d. Most values repeat
Answer: c. Every value is differentsolarwinds+1
Which is NOT a risk associated with high-cardinality predictors?
a. Overfitting
b. Increased memory usage
c. Higher computational cost
d. Lower model interpretability
Answer: d. Lower model interpretabilitydatacamp+1
In a relational database, “degree” stands for:
a. Number of rows
b. Number of columns
c. Number of tables
d. Number of databases
Answer: b. Number of columnstestbook+1
Which variable is more likely to have low cardinality?
a. Product ID
b. Gender
c. Serial number
d. Invoice number
Answer: b. Gendersolarwinds+1
How does high cardinality impact feature encoding in tree-based models?
a. No impact
b. Can split on rare categories and cause overfitting
c. Negatively impacts only OLS
d. Improves regularization
Answer: b. Can split on rare categories and cause overfittingdatacamp+1
Cardinality reduction is typically performed in ML preprocessing to:
a. Increase dimensionality
b. Decrease feature sparsity
c. Increase data leakage
d. Reduce variance
Answer: b. Decrease feature sparsitytowardsdatascience
If a column contains repeated entries for only a few categories, cardinality is:
a. High
b. Moderate
c. Low
d. Unique
Answer: c. Lowsolarwinds+1
In entity-relationship modeling, maximum cardinality defines:
a. Maximum entities in a set
b. Most relationships that one entity can participate in
c. Maximum number of features
d. Total columns in a table
Answer: b. Most relationships that one entity can participate inexamveda+1
What happens if a high-cardinality category is unseen in test data?
a. Model assigns random value
b. Model cannot encode it without prior knowledge
c. Model assigns mean
d. It has no effect
Answer: b. Model cannot encode it without prior knowledgekgptalkie+1
Which of the following relationships suggests “at least one” linkage must exist?
a. Total participation
b. Partial participation
c. Optionality
d. Null relationship
Answer: a. Total participationtestbook
Cardinality in a data model can be best described as:
a. The number of tables in a database
b. The number of attributes in an entity
c. The numerical relationships between entities
d. The schema constraints present
Answer: c. The numerical relationships between entitieswikipedia+1
Handling high-cardinality in NLP (text) features is often done by:
a. One-hot encoding each word
b. Using TF-IDF or embeddings
c. Grouping all into “other”
d. Skipping text data
Answer: b. Using TF-IDF or embeddingsdatacamp+1

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