Data Science Miscellaneous MCQ Questions and Answers | Data Science MCQs

A. To perform dimensionality reduction

B. To perform clustering

C. To reduce overfitting and improve model accuracy

D. To create decision boundaries

A. A data point with a zero value

B. An unusually extreme data point that deviates from the overall pattern

C. A data point with a high mean

D. A data point with a zero value

A. To perform text classification tasks based on conditional probabilities

B. To perform dimensionality reduction

C. To create regression models

D. To calculate p-values

A. Creating data backups

B. Sharing data publicly

C. Adding personal identifiers to data

D. Removing or altering personal identifiers from data to protect privacy

A. Descriptive statistics

B. Exploratory data analysis

C. Maximum Likelihood Estimation (MLE)

D. Data preprocessing

A. Calculating the mean squared error

B. Balancing precision and recall

C. Assessing feature importance

D. Calculating the mean squared error

A. Removing missing values

B. Visualizing data

C. Converting categorical data into numerical form

D. Applying statistical tests

A. Feature engineering

B. Regularization

C. Clustering

D. Ensemble learning

A. Variance

B. Median

C. Mode

D. Skewness

A. Visualizing data

B. Training a model with more features

C. Removing noisy data

D. Techniques for increasing the diversity of training data by applying transformations