Cost Sensitive Learning

What is the main focus of cost-sensitive learning?

• Ignoring misclassification errors

• Balancing the class distribution

• Minimizing the total misclassification cost

• Maximizing the accuracy of the model

What is the purpose of a cost matrix in cost-sensitive learning?

• Balance the class distribution

• Increase the accuracy of the model

• Assign different costs to types of misclassification errors

• Ignore the misclassification costs

What is the common name for the count of examples that are classified as negative when they are actually positive?

• False Negative

• True Negative

• False Positive

• True Positive

Which method involves transforming the training dataset to better balance the class distribution in imbalanced classification?

• Cost-Sensitive Resampling

• Cost-Sensitive Algorithms

• Cost-Sensitive Ensembles

• Threshold Optimization

What is the goal of cost-sensitive learning?

• Ignore the misclassification costs

• Balance the class distribution

• Maximize the error of the model on the training dataset

• Minimize the cost of a model on the training dataset

Which technique converts existing cost-insensitive classifiers into cost-sensitive ones without modifying them?

• MetaCost

• AdaBoost

• Decision Trees

• Logistic Regression

What is the main challenge in defining the cost matrix for some problem domains?

• Using a complex multi-dimensional function

• Ignoring the misclassification costs

• Balancing the class distribution

• Determining the equivalent dollar cost for different misclassifications

Which group of methods focuses on filtering or combining predictions from traditional machine learning models to take misclassification costs into account?

• Cost-Sensitive Ensembles

• Cost-Sensitive Algorithms

• Cost-Sensitive Resampling

• Threshold Optimization

What is the purpose of threshold optimization in cost-sensitive learning?

• Ignore the misclassification costs

• Minimize the cost of misclassification

• Maximize the accuracy of the model

• Balance the class distribution

Which approach involves modifying existing machine learning algorithms to use the cost matrix when training?

• Cost-Sensitive Algorithms

• Cost-Sensitive Resampling

• Cost-Sensitive Ensembles

• Threshold Optimization