Machine learning Workflows

Which of the following is a common technique used in data preprocessing to handle missing values?

• 
  To make t
  Data Augmentationhe data more colourful

• Imputation

• Feature Scaling

• One-Hot Encoding

What is the primary purpose of normalising data in a machine learning workflow?

• To reduce the number of features

• To handle missing values

• To bring all features to a similar scale

• To increase the dataset size

In the context of training and validation, what is the main purpose of a validation set?

• 
  To train the model

• To test the model's performance on unseen data

• To tune hyperparameters

• To increase the size of the training set

Which performance evaluation metric is most appropriate for a binary classification problem?

• Mean Squared Error (MSE)

• R-squared

• Mean Absolute Error (MAE)

• Accuracy

What is the purpose of using a confusion matrix in performance evaluation?

• To visualise the distribution of data

• To summarise the performance of a classification algorithm

• To normalise the data

• To reduce the dimensionality of the data