MCQs

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Overall MCQs for Reference

Which technique is commonly used for converting categorical variables into a numerical format in machine learning?
a. Normalization
b. One-hot encoding
c. Feature scaling
d. Dimensionality reduction
Answer: b. One-hot encodingsaidatascience+2
What does label encoding assign to categorical values?
a. Floating point values
b. Unique integer codes
c. One-hot vectors
d. Boolean values
Answer: b. Unique integer codesgeeksforgeeks
Which encoding technique is best suited for nominal categorical features?
a. Ordinal encoding
b. Hash encoding
c. One-hot encoding
d. Frequency encoding
Answer: c. One-hot encodinggeeksforgeeks+1
Ordinal encoding is most appropriate when:
a. Categories have no order
b. Categories have an inherent order
c. Data is continuous
d. Data is binary
Answer: b. Categories have an inherent ordergeeksforgeeks
What is the primary limitation of label encoding on nominal categorical features?
a. It loses category names
b. It introduces an artificial ordering
c. It creates too many columns
d. It makes data redundant
Answer: b. It introduces an artificial orderinggeeksforgeeks
Which encoding strategy creates as many new columns as there are unique values in the categorical feature?
a. Label encoding
b. Frequency encoding
c. One-hot encoding
d. Binary encoding
Answer: c. One-hot encodingsaidatascience+1
When should frequency encoding be used?
a. When categories have many unique values
b. For ordinal data
c. For binary features only
d. When categories have a clear hierarchy
Answer: a. When categories have many unique valuesgeeksforgeeks
What does binary encoding transform categorical data into?
a. Boolean arrays
b. Hexadecimal codes
c. Binary bit strings
d. Frequency counts
Answer: c. Binary bit stringsgeeksforgeeks
What is a common advantage of using hash encoding?
a. Preserves category order
b. Deals with high cardinality
c. Expands dataset width
d. Always improves model accuracy
Answer: b. Deals with high cardinalitygeeksforgeeks
Which encoder splits categorical features into multiple binary columns and uses hashing for mapping?
a. Label Encoder
b. Frequency Encoder
c. Hash Encoder
d. Ordinal Encoder
Answer: c. Hash Encodergeeksforgeeks
What is the biggest risk with one-hot encoding on features with high cardinality?
a. Data loss
b. Overfitting
c. Curse of dimensionality
d. Decoding errors
Answer: c. Curse of dimensionalitysaidatascience+1
Which of the following is NOT an encoding method?
a. Label encoding
b. One-hot encoding
c. Min-max scaling
d. Frequency encoding
Answer: c. Min-max scalingsaidatascience+1
For which data types is binary encoding typically used?
a. Continuous
b. Integer
c. High cardinality categorical
d. Boolean
Answer: c. High cardinality categoricalgeeksforgeeks
What does ordinal encoding do to the categories?
a. Groups them
b. Assigns binary values
c. Assigns ordered integers
d. Assigns random numbers
Answer: c. Assigns ordered integersgeeksforgeeks
Which method is vulnerable to creating accidental relationships between categories?
a. One-hot encoding
b. Ordinal encoding
c. Frequency encoding
d. Target encoding
Answer: b. Ordinal encodinggeeksforgeeks
In one-hot encoding, the sum of each row over encoded columns for a feature is:
a. Double the number of unique categories
b. Equal to 1
c. Variable
d. Always zero
Answer: b. Equal to 1saidatascience+1
Which package in Python provides OrdinalEncoder for ordinal encoding?
a. pandas
b. numpy
c. scikit-learn
d. seaborn
Answer: c. scikit-learngeeksforgeeks
What is a drawback of frequency encoding?
a. Incompatible with tree-based models
b. Can leak target information if not applied properly
c. Requires unique integers for each value
d. Increases feature dimensionality
Answer: b. Can leak target information if not applied properlygeeksforgeeks
What does hashing encoding NOT guarantee for categories?
a. Unique integer output
b. Reverse mapping capability
c. Fixed-length encoding
d. Suitability for large data
Answer: b. Reverse mapping capabilitygeeksforgeeks
When is target encoding used?
a. For continuous variables
b. To add Gaussian noise
c. To encode categories based on target mean
d. Only for image data
Answer: c. To encode categories based on target meangeeksforgeeks
Which encoding would be appropriate for the variable “education level” (e.g., high school < college < graduate)?
a. One-hot encoding
b. Ordinal encoding
c. Label encoding
d. Frequency encoding
Answer: b. Ordinal encodinggeeksforgeeks
Which encoding can potentially cause multicollinearity among features?
a. One-hot encoding
b. Label encoding
c. Target encoding
d. Frequency encoding
Answer: a. One-hot encodingsaidatascience+1
Which type of encoding handles cases of unseen categories in the test set efficiently?
a. One-hot encoding
b. Label encoding
c. Hash encoding
d. Frequency encoding
Answer: c. Hash encodinggeeksforgeeks
When are integer encoders inappropriate to use?
a. For ordinal categories
b. For nominal categories
c. For binary features
d. For continuous features
Answer: b. For nominal categoriesgeeksforgeeks
Binary encoding is a combination of which two techniques?
a. One-hot and frequency encoding
b. Label and hash encoding
c. One-hot and label encoding
d. Hash and label encoding
Answer: d. Hash and label encodinggeeksforgeeks
Which kind of feature encoding is best when you need to reduce the curse of dimensionality from one-hot encoding?
a. Label encoding
b. Binary encoding
c. Ordinal encoding
d. Label binarizer
Answer: b. Binary encodinggeeksforgeeks
Which method represents categorical values as the count or proportion of each class?
a. Frequency encoding
b. Ordinal encoding
c. Target encoding
d. Label encoding
Answer: a. Frequency encodinggeeksforgeeks
One-hot encoding is most suitable for variables that:
a. Have natural ordering
b. Are numeric
c. Are nominal
d. Contain only missing values
Answer: c. Are nominalsaidatascience+1
What is the main challenge in using hashing encoders?
a. Too many columns
b. Possible hash collisions
c. Slow performance
d. Requires label order
Answer: b. Possible hash collisionsgeeksforgeeks
What does target encoding risk introducing?
a. Irrelevant binary codes
b. Target leakage
c. Duplicate columns
d. Loss of information
Answer: b. Target leakagegeeksforgeeks
What is the output data type of an integer encoder?
a. Boolean
b. Integer
c. String
d. Float
Answer: b. Integergeeksforgeeks
In what scenario would one-hot encoding be discouraged?
a. Low cardinality categorical features
b. High cardinality categorical features
c. Binary categorical features
d. Ordinal features
Answer: b. High cardinality categorical featuressaidatascience+1
What is a common disadvantage shared by both label and ordinal encoding?
a. Dimensionality curse
b. Introduce false ordinal relationships
c. Too many NaNs
d. Computational inefficiency
Answer: b. Introduce false ordinal relationshipsgeeksforgeeks
Frequency encoding encodes a category as:
a. Index of occurrence
b. Its probability in data
c. A string hash value
d. One-hot bit
Answer: b. Its probability in datageeksforgeeks
Which encoder is NON-deterministic with respect to the category labels themselves?
a. One-hot encoder
b. Hash encoder
c. Label encoder
d. Ordinal encoder
Answer: b. Hash encodergeeksforgeeks
What is a key issue with using target encoding on small data sets?
a. Increased speed
b. Underfitting
c. Severe overfitting
d. NaN values
Answer: c. Severe overfittinggeeksforgeeks
Which package provides BinaryEncoder in Python?
a. scikit-learn
b. category_encoders
c. numpy
d. keras
Answer: b. category_encodersgeeksforgeeks
Which statement about hashing encoding is correct?
a. Always produces the same mapping for a given category
b. Order of output columns is meaningful
c. Multiple categories can map to the same hash value
d. Reverse decoding is always possible
Answer: c. Multiple categories can map to the same hash valuegeeksforgeeks
Which encoding technique does not provide for synchronization in data transmission?
a. NRZ-L
b. RZ
c. NRZ-I
d. Manchester
Answer: a. NRZ-Lgpberhampur
In what encoding scheme does one amplitude represent a 1 bit and zero amplitude represents a 0 bit (or vice versa)?
a. Unipolar
b. Polar
c. Bipolar
d. Biphase
Answer: a. Unipolarexamradar
The scheme that substitutes eight consecutive zeros with 000VB0VB is:
a. B4B8
b. HDB3
c. B8ZS
d. Manchester
Answer: c. B8ZSgpberhampur
Which encoding technique uses positive, negative, and zero amplitudes?
a. Unipolar
b. Polar
c. Bipolar
d. RZ
Answer: c. Bipolarexamradar+1
Which type of encoding is most suitable for data with an underlying ordinal relation but irregular spacing?
a. Hash encoding
b. Label encoding
c. Ordinal encoding
d. Target encoding
Answer: c. Ordinal encodinggeeksforgeeks
In one-hot encoding, what is a key characteristic of the resulting data matrix?
a. Sparse and binary
b. Dense and integer
c. Multicollinear and float
d. No missing values
Answer: a. Sparse and binarysaidatascience+1
Which is a potential danger of manual mapping of categories to integers without considering data distribution?
a. Losing randomization
b. Bias introduction
c. Speed improvement
d. Efficient computation
Answer: b. Bias introductiongeeksforgeeks
What is the effect of applying one-hot encoding on a binary variable?
a. Expands it to three columns
b. Keeps it as one column
c. Expands it to two columns
d. Binarizes all features
Answer: c. Expands it to two columnssaidatascience+1
Label encoding is inappropriate for which type of variable?
a. Ordinal
b. Nominal
c. Binary
d. Numeric
Answer: b. Nominalgeeksforgeeks
Which encoding method does not suffer from high memory usage with high cardinality features?
a. One-hot encoding
b. Hash encoding
c. Label encoding
d. Dummy encoding
Answer: b. Hash encodinggeeksforgeeks
Which is the best practice when encoding categorical features before applying tree-based machine learning models?
a. One-hot encoding always
b. Only use label encoding for nominal data
c. Experiment with various encoding methods
d. Ignore encoding
Answer: c. Experiment with various encoding methodsgeeksforgeeks
What should you do if unseen categories appear during the prediction phase after encoding?
a. Fail the model
b. Map to a default value or use encoding methods that can handle the unknown
c. Assign random values
d. Discard those samples
Answer: b. Map to a default value or use encoding methods that can handle the unknowngeeksforgeeks

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