ML WS CSE Unit II March 2024

To remove noise and inconsistent data ____ is needed.

• Data Cleaning

  
  

• Data Transformation

  
  

• Data Reduction

  
  

• Data Integration

  
  

Multiple data sources may be combined is called as _____

• Data Reduction

  
  

• Data Cleaning

  
  

• Data Integration

  
  

• Data Transformation

  
  

Which statement about outliers is true? 

• Outliers should be part of the training dataset but should not be present in the test data.

  
  

• Outliers should be identified and removed from a dataset. 

  
  

• The nature of the problem determines how outliers are used.

  
  

• Outliers should be part of the test dataset but should not be present in the training data.

  
  

Data set {brown, black, blue, green, red} is example of

• Continuous

• Ordinal

• Nominal

• Numeric

  
  

Correlation analysis is used for

• Handling missing values

  
  

• Identifying redundant attributes

  
  

• Handling different data formats

  
  

• Eliminating noise

  
  

Which Method is used for encoding the categorical variables?

• LabelEncoder

• OneHotEncoder

• Encoder

• All the above

Which of the following techniques would perform better for reducing the dimensions of a data set?

• Removing columns that have too many missing values

• Removing columns that have high variance in data

• Removing columns with dissimilar data trends

• None of these

LDA is an example of supervised dimensionality reduction algorithm.

• True

• False

For k cross-validation, larger k value implies more bias.

• True

• False

What is the purpose of performing cross-validation?

• To assess the predictive performance of the models

  
  

• To judge how the trained model performs outside the sample on test data

  
  

• Both A and B