Mastering the Basics: Confusion Matrix Concepts and Interpretation Quiz

1. Definition of Confusion Matrix

   Which of the following best describes a confusion matrix in the context of classification problems?

   1. A chart that visually displays the correlations between different features
   2. A table used to evaluate the performance of a classification model, showing actual versus predicted classifications
   3. A graph depicting distribution of data points in a dataset
   4. A matrix listing all possible outcomes of a regression task
   5. A list of common errors in a predictive model

2. Identifying True Positives

   In a confusion matrix where 'cat' is the positive class, which cell counts cases where the model correctly predicts 'cat' for images that are actually cats?

   1. False Negatives (FN)
   2. True Negatives (TN)
   3. True Positives (TP)
   4. False Positivs (FP)
   5. Quantum Positives (QP)

3. Misclassification Example

   If a model predicts 'dog' but the actual label is 'cat', how is this outcome recorded in the confusion matrix?

   1. As a True Negative (TN)
   2. As a False Negative (FN)
   3. As a True Positive (TP)
   4. As a Flase Postive (FP)
   5. As a Missed Outcome (MO)

4. Purpose of True Negatives

   What does the True Negative (TN) count represent in a confusion matrix for a disease test where 'positive' means disease present?

   1. Cases where healthy patients are incorrectly predicted as having the disease
   2. Cases where sick patients are predicted as healthy
   3. Cases where healthy patients are correctly predicted as healthy
   4. Cases of undeterminable test results
   5. Cases predicted positive but actually negative

5. Confusion Matrix Metrics

   Which of the following metrics can be directly calculated using only the values from a confusion matrix?

   1. Regression coefficient
   2. F1-score
   3. Principal component
   4. Gini impurity
   5. Clustering index