Computer Science & IT

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Q. What is the purpose of cookies in web protocols?
  • A. Store user preferences
  • B. Track sessions
  • C. Authenticate users
  • D. All of the above
Q. What is the purpose of cross-validation in machine learning?
  • A. To increase the size of the training dataset
  • B. To assess how the results of a statistical analysis will generalize to an independent dataset
  • C. To reduce the complexity of the model
  • D. To improve the speed of training
Q. What is the purpose of cross-validation in model evaluation?
  • A. To increase the size of the dataset
  • B. To ensure the model is not overfitting
  • C. To visualize model performance
  • D. To reduce training time
Q. What is the purpose of cross-validation in model selection?
  • A. To increase the size of the training dataset
  • B. To assess how the results of a statistical analysis will generalize to an independent dataset
  • C. To reduce overfitting by simplifying the model
  • D. To improve the accuracy of the model
Q. What is the purpose of cross-validation in supervised learning?
  • A. To increase the size of the training dataset
  • B. To assess how the results of a statistical analysis will generalize to an independent dataset
  • C. To reduce the dimensionality of the dataset
  • D. To improve the model's accuracy on the training set
Q. What is the purpose of cross-validation in the context of linear regression?
  • A. To increase the number of features
  • B. To assess the model's performance on unseen data
  • C. To reduce the training time
  • D. To improve the model's accuracy
Q. What is the purpose of cross-validation?
  • A. To increase the size of the training dataset
  • B. To assess how the results of a statistical analysis will generalize to an independent dataset
  • C. To reduce the complexity of the model
  • D. To improve the interpretability of the model
Q. What is the purpose of dropout in neural networks?
  • A. To increase the learning rate
  • B. To prevent overfitting
  • C. To enhance feature extraction
  • D. To reduce computational cost
Q. What is the purpose of error control in data transmission?
  • A. To increase transmission speed
  • B. To ensure data integrity
  • C. To reduce latency
  • D. To manage network congestion
Q. What is the purpose of feature importance in Random Forests?
  • A. To reduce the number of trees.
  • B. To identify the most influential features.
  • C. To visualize the tree structure.
  • D. To increase the model's complexity.
Q. What is the purpose of feature scaling in machine learning?
  • A. To increase the number of features
  • B. To improve the performance of the model
  • C. To reduce the size of the dataset
  • D. To convert categorical data to numerical
Q. What is the purpose of feature selection in model training?
  • A. To increase the number of features
  • B. To reduce the complexity of the model
  • C. To improve the training speed
  • D. To ensure all features are used
Q. What is the purpose of HTTP headers?
  • A. To define the structure of the message
  • B. To provide metadata about the request or response
  • C. To encrypt the data
  • D. To establish a connection
Q. What is the purpose of hyperparameter tuning in model selection?
  • A. To adjust the model's architecture
  • B. To select the best features
  • C. To improve model performance
  • D. To visualize results
Q. What is the purpose of hyperparameter tuning?
  • A. To select the best features
  • B. To improve model performance by optimizing parameters
  • C. To evaluate model accuracy
  • D. To visualize data distributions
Q. What is the purpose of intermediate code in a compiler?
  • A. To optimize the source code
  • B. To provide a platform-independent representation
  • C. To perform lexical analysis
  • D. To generate machine code
Q. What is the purpose of model selection in machine learning?
  • A. To choose the best algorithm for the data
  • B. To preprocess the data
  • C. To visualize the data
  • D. To deploy the model
Q. What is the purpose of model selection?
  • A. To improve the accuracy of a single model
  • B. To choose the best model from a set of candidates
  • C. To reduce the dimensionality of the data
  • D. To increase the size of the dataset
Q. What is the purpose of monitoring a deployed machine learning model?
  • A. To ensure the model is still accurate over time
  • B. To collect more training data
  • C. To improve the model's architecture
  • D. To reduce the model's size
Q. What is the purpose of monitoring a deployed model?
  • A. To ensure it is still accurate and performing well
  • B. To retrain the model automatically
  • C. To visualize data inputs
  • D. To reduce model complexity
Q. What is the purpose of normalization in feature engineering?
  • A. To increase the range of feature values
  • B. To ensure all features contribute equally to the distance calculations
  • C. To reduce the number of features
  • D. To eliminate outliers
Q. What is the purpose of normalization in the context of neural networks?
  • A. To increase the number of features
  • B. To ensure all input features have similar scales
  • C. To reduce the size of the dataset
  • D. To improve the model's interpretability
Q. What is the purpose of one-hot encoding in feature engineering?
  • A. To normalize numerical features
  • B. To convert categorical variables into a numerical format
  • C. To reduce dimensionality
  • D. To handle missing values
Q. What is the purpose of pruning in Decision Trees?
  • A. To increase the depth of the tree
  • B. To remove unnecessary branches
  • C. To add more features
  • D. To improve computational efficiency
Q. What is the purpose of register allocation in code generation?
  • A. To minimize the use of memory
  • B. To assign variables to CPU registers
  • C. To optimize the execution speed of loops
  • D. To eliminate redundant calculations
Q. What is the purpose of regularization in linear regression?
  • A. To increase the number of features
  • B. To reduce the risk of overfitting
  • C. To improve the interpretability of the model
  • D. To ensure normality of residuals
Q. What is the purpose of regularization in regression models?
  • A. To increase the model complexity
  • B. To reduce the training time
  • C. To prevent overfitting by penalizing large coefficients
  • D. To improve the interpretability of the model
Q. What is the purpose of regularization in supervised learning?
  • A. To increase the complexity of the model
  • B. To prevent overfitting
  • C. To improve training speed
  • D. To enhance feature selection
Q. What is the purpose of semantic rules in syntax-directed translation?
  • A. To define the syntax of the programming language
  • B. To specify the actions to be taken during parsing
  • C. To determine the types of variables
  • D. To optimize the final machine code
Q. What is the purpose of subnetting in IP addressing?
  • A. To increase the number of available IP addresses
  • B. To improve network performance and security
  • C. To simplify routing
  • D. To enable NAT
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